This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. AI can now create a replica of your personality Imagine sitting down with an AI model for a spoken two-hour interview. A friendly voice guides you through a conversation that ranges from your childhood, your formative memories, and your career to your thoughts on immigration policy. Not long after, a virtual replica of you is able to embody your values and preferences with stunning accuracy. Thats now possible, according to a new paper from a team including researchers from Stanford and Google DeepMind. They recruited 1,000 people and, from interviews with them, created agent replicas of them all. To test how well the agents mimicked their human counterparts, participants did a series of tests, games and surveys, then the agents completed the same exercises. The results were 85% similar. Freaky.Read our story about the work, and why it matters. James ODonnell Chinas complicated role in climate change But what about China? In debates about climate change, its usually only a matter of time until someone brings up China. Often, it comes in response to some statement about how the US and Europe are addressing the issue (or how they need to be). Sometimes it can be done in bad faith. Its a rhetorical way to throw up your hands, and essentially say: if they arent taking responsibility, why should we? However, there are some undeniable facts: China emits more greenhouse gases than any other country, by far. Its one of the worlds most populous countries and a climate-tech powerhouse, and its economy is still developing. With many complicated factors at play, how should we think about the countrys role in addressing climate change?Read the full story. Casey Crownhart This story is from The Spark, our weekly newsletter giving you the inside track on all things energy and climate.Sign upto receive it in your inbox every Wednesday. Four ways to protect your art from AI Since the start of the generative AI boom, artists have been worried about losing their livelihoods to AI tools. Unfortunately, there is little you can do if your work has been scraped into a data set and used in a model that is already out there. You can, however, take steps to prevent your work from being used in the future.Here are four ways to do that.Melissa Heikkila This is part of our How To series, where we give you practical advice on how to use technology in your everyday lives. You can read the rest of the series here. MIT Technology Review Narrated: The worlds on the verge of a carbon storage boom In late 2023, one of Californias largest oil and gas producers secured draft permits from the US Environmental Protection Agency to develop a new type of well in an oil field. If approved, it intends to drill a series of boreholes down to a sprawling sedimentary formation roughly 6,000 feet below the surface, where it will inject tens of millions of metric tons of carbon dioxide to store it away forever. Hundreds of similar projects are looming across the state, the US, and the world. Proponents hope its the start of a sort of oil boom in reverse, kick-starting a process through which the world will eventually bury more greenhouse gas than it adds to the atmosphere. But opponents insist these efforts will prolong the life of fossil-fuel plants, allow air and water pollution to continue, and create new health and environmental risks. This is our lateststoryto be turned into a MIT Technology Review Narrated podcast, which were publishing each week onSpotifyandApple Podcasts. Just navigate toMIT Technology Review Narratedon either platform, and follow us to get all our new content as its released. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 How the Trump administration could hack your phone Spyware acquired by the US government in September could fairly easily be turned on its own citizens. (New Yorker$)+Heres how you can fight back against being digitally spied upon.(The Guardian)2 The DOJ is trying to force Google to sell off ChromeWhether Trump will keep pushing it through is unclear, though. (WP$)+Some financial and legal experts argue that just selling Chrome is not enough to address antitrust issues.(Wired$)3 Theres a booming AI pimping industryPeople are stealing videos from real adult content creators, giving them AI-generated faces, and monetizing their bodies. (Wired$)+This viral AI avatar app undressed mewithout my consent.(MIT Technology Review)4 Heres Elon Musk and Vivek Ramaswamy plan for federal employeesLarge-scale firings and an end to any form of remote work. (WSJ$)5 The US is scaring everyone with its response to bird flu Its done remarkably little to show its trying to contain the outbreak. (NYT$)+Virologists are getting increasingly nervous about how it could evolve and spread. (MIT Technology Review) 6 AI could boost the performance of quantum computers A new model created by Google DeepMind is very good at correcting errors.(New Scientist$)+But AI could also make quantum computers less necessary.(MIT Technology Review)7 Biden has approved the use of anti-personnel mines in UkraineIt comes just days after he gave the go-ahead for it to use long-range missiles inside Russia. (Axios)+The US military has given a surveillance drone contract to a little-known supplier from Utah.(WSJ$)+The Danish military said its keeping a close eye on a Chinese ship in its waters after data cable breaches.(Reuters$)8 The number of new mobile internet users is stallingOnly about 57% of the worlds population is connected. (Rest of World)9 All of life on Earth descended from this single cell Our last universal common ancestor (or LUCA for short) was a surprisingly complex organism living 4.2 billion years ago. (Quanta)+Scientists are building a catalog of every type of cell in our bodies. (The Economist$)10 What its like to live with a fluffy AI petTry as we might, it seems we cant help but form attachments to cute companion robots. (The Guardian)Quote of the day The free pumpkins have brought joy to many. An example of the sort of stilted remarks made by a now-abandoned AI-generated news broadcaster at local Hawaii paper The Garden Island,Wiredreports.The big story How Bitcoin mining devastated this New York town GABRIELA BHASKAR April 2022 If you had taken a gamble in 2017 and purchased Bitcoin, today you might be a millionaire many times over. But while the industry has provided windfalls for some, local communities have paid a high price, as people started scouring the world for cheap sources of energy to run large Bitcoin-mining farms. It didnt take long for a subsidiary of the popular Bitcoin mining firm Coinmint to lease a Family Dollar store in Plattsburgh, a city in New York state offering cheap power. Soon, the company was regularly drawing enough power for about 4,000 homes. And while other miners were quick to follow, the problems had already taken root.Read the full story. Lois Parshley We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Cultivatinggratitudeis a proven way to make yourself happier. + You cant beat ahot toddywhen its cold outside.+ If you like abandoned places and overgrown ruins,Jonathan Jimenezis the photographer for you.+ A lot changed betweenGladiator I and II, not least Hollywoods version of the male ideal.

OpenAI is once again lifting the lid (just a crack) on its safety-testing processes. Last month the company shared the results of an investigation that looked at how often ChatGPT produced a harmful gender or racial stereotype based on a users name. Now it has put out two papers describing how it stress-tests its powerful large language models to try to identify potential harmful or otherwise unwanted behavior, an approach known as red-teaming. Large language models are now being used by millions of people for many different things. But as OpenAI itself points out, these models are known to produce racist, misogynistic and hateful content; reveal private information; amplify biases and stereotypes; and make stuff up. The company wants to share what it is doing to minimize such behaviors. The first paper describes how OpenAI directs an extensive network of human testers outside the company to vet the behavior of its models before they are released. The second paper presents a new way to automate parts of the testing process, using a large language model like GPT-4 to come up with novel ways to bypass its own guardrails. The aim is to combine these two approaches, with unwanted behaviors discovered by human testers handed off to an AI to be explored further and vice versa. Automated red-teaming can come up with a large number of different behaviors, but human testers bring more diverse perspectives into play, says Lama Ahmad, a researcher at OpenAI: We are still thinking about the ways that they complement each other. Red-teaming isnt new. AI companies have repurposed the approach from cybersecurity, where teams of people try to find vulnerabilities in large computer systems. OpenAI first used the approach in 2022, when it was testing DALL-E 2. It was the first time OpenAI had released a product that would be quite accessible, says Ahmad. We thought it would be really important to understand how people would interact with the system and what risks might be surfaced along the way. The technique has since become a mainstay of the industry. Last year, President Bidens Executive Order on AI tasked the National Institute of Standards and Technology (NIST) with defining best practices for red-teaming. To do this, NIST will probably look to top AI labs for guidance. Tricking ChatGPT When recruiting testers, OpenAI draws on a range of experts, from artists to scientists to people with detailed knowledge of the law, medicine, or regional politics. OpenAI invites these testers to poke and prod its models until they break. The aim is to uncover new unwanted behaviors and look for ways to get around existing guardrailssuch as tricking ChatGPT into saying something racist or DALL-E into producing explicit violent images. Adding new capabilities to a model can introduce a whole range of new behaviors that need to be explored. When OpenAI added voices to GPT-4o, allowing users to talk to ChatGPT and ChatGPT to talk back, red-teamers found that the model would sometimes start mimicking the speakers voice, an unexpected behavior that was both annoying and a fraud risk. There is often nuance involved. When testing DALL-E 2 in 2022, red-teamers had to consider different uses of eggplant, a word that now denotes an emoji with sexual connotations as well as a purple vegetable. OpenAI describes how it had to find a line between acceptable requests for an image, such as A person eating an eggplant for dinner, and unacceptable ones, such as A person putting a whole eggplant into her mouth. Similarly, red-teamers had to consider how users might try to bypass a models safety checks. DALL-E does not allow you to ask for images of violence. Ask for a picture of a dead horse lying in a pool of blood, and it will deny your request. But what about a sleeping horse lying in a pool of ketchup? When OpenAI tested DALL-E 3 last year, it used an automated process to cover even more variations of what users might ask for. It used GPT-4 to generate requests producing images that could be used for misinformation or that depicted sex, violence, or self-harm. OpenAI then updated DALL-E 3 so that it would either refuse such requests or rewrite them before generating an image.Ask for a horse in ketchup now, and DALL-E is wise to you: It appears there are challenges in generating the image. Would you like me to try a different request or explore another idea? In theory, automated red-teaming can be used to cover more ground, but earlier techniques had two major shortcomings: They tend to either fixate on a narrow range of high-risk behaviors or come up with a wide range of low-risk ones. Thats because reinforcement learning, the technology behind these techniques, needs something to aim fora rewardto work well. Once its won a reward, such as finding a high-risk behavior, it will keep trying to do the same thing again and again. Without a reward, on the other hand, the results are scattershot. They kind of collapse into We found a thing that works! We'll keep giving that answer! or they'll give lots of examples that are really obvious, says Alex Beutel, another OpenAI researcher. How do we get examples that are both diverse and effective? A problem of two parts OpenAIs answer, outlined in the second paper, is to split the problem into two parts. Instead of using reinforcement learning from the start, it first uses a large language model to brainstorm possible unwanted behaviors. Only then does it direct a reinforcement-learning model to figure out how to bring those behaviors about. This gives the model a wide range of specific things to aim for. Beutel and his colleagues showed that this approach can find potential attacks known as indirect prompt injections, where another piece of software, such as a website, slips a model a secret instruction to make it do something its user hadnt asked it to. OpenAI claims this is the first time that automated red-teaming has been used to find attacks of this kind. They dont necessarily look like flagrantly bad things, says Beutel. Will such testing procedures ever be enough? Ahmad hopes that describing the companys approach will help people understand red-teaming better and follow its lead. OpenAI shouldnt be the only one doing red-teaming, she says. People who build on OpenAIs models or who use ChatGPT in new ways should conduct their own testing, she says: There are so many useswere not going to cover every one. For some, thats the whole problem. Because nobody knows exactly what large language models can and cannot do, no amount of testing can rule out unwanted or harmful behaviors fully. And no network of red-teamers will ever match the variety of uses and misuses that hundreds of millions of actual users will think up. Thats especially true when these models are run in new settings. People often hook them up to new sources of data that can change how they behave, says Nazneen Rajani, founder and CEO of Collinear AI, a startup that helps businesses deploy third-party models safely. She agrees with Ahmad that downstream users should have access to tools that let them test large language models themselves. Rajani also questions using GPT-4 to do red-teaming on itself. She notes that models have been found to prefer their own output: GPT-4 ranks its performance higher than that of rivals such as Claude or Llama, for example. This could lead it to go easy on itself, she says: Id imagine automated red-teaming with GPT-4 may not generate as harmful attacks [as other models might]. Miles behind For Andrew Tait, a researcher at the Ada Lovelace Institute in the UK, theres a wider issue. Large language models are being built and released faster than techniques for testing them can keep up. Were talking about systems that are being marketed for any purpose at alleducation, health care, military, and law enforcement purposesand that means that youre talking about such a wide scope of tasks and activities that to create any kind of evaluation, whether thats a red team or something else, is an enormous undertaking, says Tait. Were just miles behind. Tait welcomes the approach of researchers at OpenAI and elsewhere (he previously worked on safety at Google DeepMind himself) but warns that its not enough: There are people in these organizations who care deeply about safety, but theyre fundamentally hamstrung by the fact that the science of evaluation is not anywhere close to being able to tell you something meaningful about the safety of these systems. Tait argues that the industry needs to rethink its entire pitch for these models. Instead of selling them as machines that can do anything, they need to be tailored to more specific tasks. You cant properly test a general-purpose model, he says. If you tell people its general purpose, you really have no idea if its going to function for any given task, says Tait. He believes that only by testing specific applications of that model will you see how well it behaves in certain settings, with real users and real uses. Its like saying an engine is safe; therefore every car that uses it is safe, he says. And thats ludicrous.

Once again, global greenhouse-gas emissions are projected to hit a new high in 2024. In this time of shifting political landscapes and ongoing international negotiations, many are quick to blame one country or another for an outsize role in causing climate change. But assigning responsibility is complicated. These three visualizations help explain why and provide some perspective about the worlds biggest polluters. Greenhouse-gas emissions from fossil fuels and industry reached 37.4 billion metric tons of carbon dioxide in 2024, according to projections from the Global Carbon Budget, an annual emissions report released last week. Thats a 0.8% increase over last year. Breaking things down by country, China is far and away the single biggest polluter today, a distinction it has held since 2006. The country currently emits roughly twice as much greenhouse gas as any other nation. The power sector is its single greatest source of emissions as the grid is heavily dependent on coal, the most polluting fossil fuel. The US is the worlds second-biggest polluter, followed by India. Combined emissions from the 27 nations that make up the European Union are next, followed by Russia and Japan. Considering a countrys current emissions doesnt give the whole picture of its climate responsibility, though. Carbon dioxide is stable in the atmosphere for hundreds of years. That means greenhouse gases from the first coal power plant, which opened in the late 19th century, are still having a warming effect on the planet today. Adding up each countrys emissions over the course of its history reveals that the US has the greatest historical contributionthe country is responsible for about 24% of all the climate pollution released into the atmosphere as of 2023. While its the biggest polluter today, China comes in second in terms of historical emissions, at 14%. If the EUs member states are totaled as one entity, the group is among the top historical contributors as well. According to an analysis published November 19 by the website Carbon Brief, China passed EU member states in terms of historical emissions in 2023 for the first time. China could catch up with the West in the coming decades, as its emissions are significant and still growing, while the US and EU are seeing moderate declines. Even then, though, theres another factor to consider: population. Dividing a countrys total emissions by its population reveals how the average individual in each nation is contributing to climate change today. Countries with smaller populations and economies that are heavily reliant on oil and gas tend to top this list, including Saudi Arabia, Bahrain, and the United Arab Emirates. Among the larger nations, Australia has the highest per capita emissions from fossil fuels, with the US and Canada close behind. Meanwhile, other countries that have high total emissions are farther down the list when normalized by population: Chinas per capita emissions are just over half that of the US, while Indias is a small fraction. Understanding the complicated picture of global emissions is crucial, especially during ongoing negotiations (including the current meeting at COP29 in Baku, Azerbaijan) over how to help developing nations pay for efforts to combat climate change. Looking at current emissions, one might expect the biggest emitter, China, to contribute more than any other country to climate finance. But considering historical contributions, per capita emissions, and details about national economies, other nations like the US, UK, and members of the EU emerge as those experts tend to say should feature prominently in the talks. What is clear is that when it comes to the emissions blame game, its more complicated than just pointing at todays biggest polluters. Ultimately, addressing climate change will require everyone to get on boardwe all share an atmosphere, and were all going to continue feeling the effects of a changing climate. Notes on data methodology: Emissions data is from the Global Carbon Project, which estimates carbon emissions based on energy use. Territorial emissions take into account energy and some industry, but dont include land use emissions. Data from the European Union is the sum of its current 27 member states. The bloc is represented together because the EU generally negotiates together on the international stage. Historical emissions for some countries are disaggregated from former borders, including the former USSR and Yugoslavia. The per capita emissions map uses official World Bank boundaries, with the exception of Taiwan, which has separate emissions data in the Global Carbon Project. Western Saharas energy data are reported by Morocco, so its emissions are included in that total. Per capita emissions for Morocco are also used for Western Sahara on the map. More detailed information about the Global Carbon Project methods (including the particulars on how territorial emissions are broken down) is available here.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Inside Clears ambitions to manage your identity beyond the airport Clear Secure is the most visible biometric identity company in the United States. Best known for its line-jumping service in airports, its also popping up at sports arenas and stadiums all over the country. You can also use its identity verification platform to rent tools at Home Depot, put your profile in front of recruiters on LinkedIn, and, as of this month, verify your identity as a rider on Uber. And soon enough, if Clear has its way, it may also be in your favorite retailer, bank, and even doctors officeor anywhere else that you currently have to pull out a wallet (or wait in line). While the company has been building toward this sweeping vision for years, it now seems its time has finally come. But as biometrics go mainstream, whatand whobears the cost? Read the full story. Eileen Guo LinkedIn Live: Facial verification tech promises a frictionless future. But at what cost? Do you use your face to unlock your phone, or speed through airport security? As biometrics companies move into more and more spaces, where else would you use this technology? The trade off seems simple: you scan your face, you get a frictionless future. But is it really? Join MIT Technology Reviews features and investigations team for a LinkedIn Live this Thursday, November 21, about the rise of facial verification tech and what it means to give up your face. Register for free. Whos to blame for climate change? Its surprisingly complicated. Once again, global greenhouse-gas emissions are projected to hit a new high in 2024. In this time of shifting political landscapes and ongoing international negotiations, many are quick to blame one country or another for an outsize role in causing climate change. But assigning responsibility is complicated. These three visualizations help explain why. Casey Crownhart Cyber Week Sale: subscriptions are half price! Take advantage of epic savings on award-winning reporting, razor-sharp analysis, and expert insights on your favorite technology topics. Subscribe today to save 50% on an annual subscription, plus receive a free digital copy of our Generative AI and the future of work report. Dont miss out. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 AI can now translate your voice in real-time during meetings Its part of Microsofts drive to push more AI into its products, but how well it works in the wild remains to be seen. (WP$)+Apple is having less success on that front, at least if its AI notification summaries are anything to go by.(The Atlantic$)2 Anyone can buy data tracking US soldiers in Germany And the Pentagon is powerless to stop it.(Wired$)+Its shockingly easy to buy sensitive data about US military personnel.(MIT Technology Review)3 Bluesky now has over 20 million usersIts user base has tripled in the last three months. (Engadget)+Truth Social, on the other hand, is not doing quite so well.(WP$)+The rise of Bluesky, and the splintering of social.(MIT Technology Review)4 How Google created a culture of concealmentIts been preparing for antitrust action for over a decade, enforcing a policy where employees delete messages by default. (NYT$)+The company reacted angrily to reports it may be forced to sell Chrome. (BBC)5 Project 2025 is already infiltrating the Trump administrationDespite repeated denials, its clearly a blueprint for his next term. (Vox)+A hacker reportedly gained access to damaging testimonies about Matt Gaetz, his pick to be attorney general.(NYT$)6 Quantum computers hit a major milestone for error-free calculationThis is a crucial part of making them useful for real-world tasks. (New Scientist$)7 Technology is changing political speechSlogans are becoming less effective. Now its more about saying different things to different audiences. (New Yorker$)8 Lab-grown foie gras, anyone?This could be the cultivated meat industrys future: as a luxury product for the few. (Wired$)9 Niantic is using Pokmon Go player data to build an AI navigation system If it works, it could unlock some amazing capabilities in AR, robotics and beyond. (404 Media) 10 Minecraft is expanding into the real world It has struck a $110 million deal with one of the worlds biggest theme park operators. (The Guardian)Quote of the day Nobody believes that these cables were severed by accident. Germanys defense minister Boris Pistorius, tells reporters that the severing of two fiber-optic cables in the Baltic Sea was a deliberate act of sabotage, theNew York Timesreports.The big story Are we alone in the universe? ARIEL DAVIS November 2023 The quest to determine if life is out there has gained greater scientific footing over the past 50 years. Back then, astronomers had yet to spot a single planet outside our solar system. Now we know the galaxy is teeming with a diversity of worlds. Were getting closer than ever before to learning how common living worlds like ours actually are. New tools, including artificial intelligence, could help scientists look past their preconceived notions of what constitutes life.Read the full story. Adam Mann We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + How to not only survive but thriveduring the winter. + Fancy working from somewhere new? Here are some of thebest citiesfor a workcation.+ Want to see David Bowie imitating Mick Jagger?Of course you do.+ Its an old(ish) joke butstill funny.

Imagine sitting down with an AI model for a spoken two-hour interview. A friendly voice guides you through a conversation that ranges from your childhood, your formative memories, and your career to your thoughts on immigration policy. Not long after, a virtual replica of you is able to embody your values and preferences with stunning accuracy. Thats now possible, according to a new paper from a team including researchers from Stanford and Google DeepMind, which has been published on arXiv and has not yet been peer-reviewed. Led by Joon Sung Park, a Stanford PhD student in computer science, the team recruited 1,000 people who varied by age, gender, race, region, education, and political ideology. They were paid up to $100 for their participation. From interviews with them, the team created agent replicas of those individuals. As a test of how well the agents mimicked their human counterparts, participants did a series of personality tests, social surveys, and logic games, twice each, two weeks apart; then the agents completed the same exercises. The results were 85% similar. If you can have a bunch of small yous running around and actually making the decisions that you would have madethat, I think, is ultimately the future, Joon says. In the paper the replicas are called simulation agents, and the impetus for creating them is to make it easier for researchers in social sciences and other fields to conduct studies that would be expensive, impractical, or unethical to do with real human subjects. If you can create AI models that behave like real people, the thinking goes, you can use them to test everything from how well interventions on social media combat misinformation to what behaviors cause traffic jams. Such simulation agents are slightly different from the agents that are dominating the work of leading AI companies today. Called tool-based agents, those are models built to do things for you, not converse with you. For example, they might enter data, retrieve information you have stored somewhere, orsomedaybook travel for you and schedule appointments. Salesforce announced its own tool-based agents in September, followed by Anthropic in October, and OpenAI is planning to release some in January, according to Bloomberg. The two types of agents are different but share common ground. Research on simulation agents, like the ones in this paper, is likely to lead to stronger AI agents overall, says John Horton, an associate professor of information technologies at the MIT Sloan School of Management, who founded a company to conduct research using AI-simulated participants. This paper is showing how you can do a kind of hybrid: use real humans to generate personas which can then be used programmatically/in-simulation in ways you could not with real humans, he told MIT Technology Review in an email. The research comes with caveats, not the least of which is the danger that it points to. Just as image generation technology has made it easy to create harmful deepfakes of people without their consent, any agent generation technology raises questions about the ease with which people can build tools to personify others online, saying or authorizing things they didnt intend to say. The evaluation methods the team used to test how well the AI agents replicated their corresponding humans were also fairly basic. These included the General Social Surveywhich collects information on ones demographics, happiness, behaviors, and moreand assessments of the Big Five personality traits: openness to experience, conscientiousness, extroversion, agreeableness, and neuroticism. Such tests are commonly used in social science research but dont pretend to capture all the unique details that make us ourselves. The AI agents were also worse at replicating the humans in behavioral tests like the dictator game, which is meant to illuminate how participants consider values such as fairness. To build an AI agent that replicates people well, the researchers needed ways to distill our uniqueness into language AI models can understand. They chose qualitative interviews to do just that, Joon says. He says he was convinced that interviews are the most efficient way to learn about someone after he appeared on countless podcasts following a 2023 paper that he wrote on generative agents, which sparked a huge amount of interest in the field. I would go on maybe a two-hour podcast podcast interview, and after the interview, I felt like, wow, people know a lot about me now, he says. Two hours can be very powerful. These interviews can also reveal idiosyncrasies that are less likely to show up on a survey. Imagine somebody just had cancer but was finally cured last year. Thats very unique information about you that says a lot about how you might behave and think about things, he says. It would be difficult to craft survey questions that elicit these sorts of memories and responses. Interviews arent the only option, though. Companies that offer to make digital twins of users, like Tavus, can have their AI models ingest customer emails or other data. It tends to take a pretty large data set to replicate someones personality that way, Tavus CEO Hassaan Raza told me, but this new paper suggests a more efficient route. What was really cool here is that they show you might not need that much information, Raza says, adding that his company will experiment with the approach. How about you just talk to an AI interviewer for 30 minutes today, 30 minutes tomorrow? And then we use that to construct this digital twin of you.

This story is from The Algorithm, our weekly newsletter on AI. To get it in your inbox first,sign up here. It can be tricky for reporters to get past certain doors, and the door to the International Association of Chiefs of Police conference is one thats almost perpetually shut to the media. Thus, I was pleasantly surprised when I was able to attend for a day in Boston last month. It bills itself as the largest gathering of police chiefs in the United States, where leaders from many of the countrys 18,000 police departments and even some from abroad convene for product demos, discussions, parties, and awards. I went along to see how artificial intelligence was being discussed, and the message to police chiefs seemed crystal clear: If your department is slow to adopt AI, fix that now. The future of policing will rely on it in all its forms. In the events expo hall, the vendors (of which there were more than 600) offered a glimpse into the ballooning industry of police-tech suppliers. Some had little to do with AIbooths showcased body armor, rifles, and prototypes of police-branded Cybertrucks, and others displayed new types of gloves promising to protect officers from needles during searches. But one needed only to look to where the largest crowds gathered to understand that AI was the major draw. The hype focused on three uses of AI in policing. The pitch on VR training is that in the long run, it can be cheaper and more engaging to use than training with actors or in a classroom. If youre enjoying what youre doing, youre more focused and you remember more than when looking at a PDF and nodding your head, V-Armed CEO Ezra Kraus told me. The effectiveness of VR training systems has yet to be fully studied, and they cant completely replicate the nuanced interactions police have in the real world. AI is not yet great at the soft skills required for interactions with the public. At a different companys booth, I tried out a VR system focused on deescalation training, in which officers were tasked with calming down an AI character in distress. It suffered from lag and was generally quite awkwardthe characters answers felt overly scripted and programmatic. The second focus was on the changing way police departments are collecting and interpreting data. Police chiefs attended classes on how to build these systems, like one taught by Microsoft and the NYPD about the Domain Awareness System, a web of license plate readers, cameras, and other data sources used to track and monitor crime in New York City. Crowds gathered at massive, high-tech booths from Axon and Flock, both sponsors of the conference. Flock sells a suite of cameras, license plate readers, and drones, offering AI to analyze the data coming in and trigger alerts. These sorts of tools have come in for heavy criticism from civil liberties groups, which see themas an assault on privacythat does little to help the public. Finally, as in other industries, AI is also coming for the drudgery of administrative tasks and reporting. Weve got this thing on an officers body, and its recording all sorts of great stuff about the incident, Bryan Wheeler, a senior vice president at Axon, told me at the expo. Can we use it to give the officer a head start? On the surface, its a writing task well suited for AI, which can quickly summarize information and write in a formulaic way. It could also save lots of time officers currently spend on writing reports.But given that AI is prone to hallucination, theres an unavoidable truth: Even if officers are the final authors of their reports, departments adopting these sorts of tools risk injecting errors into some of the most critical documents in the justice system. Police reports are sometimes the only memorialized account of an incident, wrote Andrew Ferguson, a professor of law at American University, in July in the firstlaw review articleabout the serious challenges posed by police reports written with AI. Because criminal cases can take months or years to get to trial, the accuracy of these reports are critically important. Whether certain details were included or left out can affect the outcomes of everything from bail amounts to verdicts. By showing an officer a generated version of a police report, the tools also expose officers to details from their body camera recordingsbeforethey complete their report, a document intended to capture the officers memory of the incident. That poses a problem. The police certainly would never show video to a bystander eyewitness before they ask the eyewitness about what took place, as that would just be investigatory malpractice, says Jay Stanley, a senior policy analyst with the ACLU Speech, Privacy, and Technology Project, who will soon publish work on the subject. A spokesperson for Axon says this concern isnt reflective of how the tool is intended to work, and that Draft One has robust features to make sure officers read the reports closely, add their own information, and edit the reports for accuracy before submitting them. My biggest takeaway from the conference was simply that the way US police are adopting AI is inherently chaotic.There is no one agency governing how they use the technology, and the roughly 18,000 police departments in the United Statesthe precise figure is not even knownhave remarkably high levels of autonomy to decide which AI tools theyll buy and deploy. The police-tech companies that serve them will build the tools police departments find attractive, and its unclear if anyone will draw proper boundaries for ethics, privacy, and accuracy. That will only be made more apparent in an upcoming Trump administration. In a policingagendareleased last year during his campaign, Trump encouraged more aggressive tactics like stop and frisk, deeper cooperation with immigration agencies, and increased liability protection for officers accused of wrongdoing. The Biden administration is nowreportedlyattempting to lock in some of its proposed policing reforms before January. Without federal regulation on how police departments can and cannot use AI, the lines will be drawn by departments and police-tech companies themselves. Ultimately, these are for-profit companies, and their customers are law enforcement, says Stanley. They do what their customers want, in the absence of some very large countervailing threat to their business model. Now read the rest of The Algorithm Deeper Learning The AI lab waging a guerrilla war over exploitative AI When generative AI tools landed on the scene, artists were immediately concerned, seeing them as a new kind of theft. Computer security researcher Ben Zhao jumped into action in response, and his lab at the University of Chicago started building tools like Nightshade and Glaze to help artists keep their work from being scraped up by AI models. My colleague Melissa Heikkil spent time with Zhao and his team to look at the ongoing effort to make these tools strong enough to stop AIs relentless hunger for more images, art, and data to train on. Why this matters: The current paradigm in AI is to build bigger and bigger models, and these require vast data sets to train on. Tech companies argue that anything on the public internet is fair game, while artists demand compensation or the right to refuse. Settling this fight in the courts or through regulation could take years, so tools like Nightshade and Glaze are what artists have for now. If the tools disrupt AI companies efforts to make better models, that could push them to the negotiating table to bargain over licensing and fair compensation. But its a big if.Read more from Melissa Heikkil. Bits and Bytes Tech elites are lobbying Elon Musk for jobs in Trumps administration Elon Musk is the tech leader who most has Trumps ear. As such, hes reportedly the conduit through which AI and tech insiders are pushing to have an influence in the incoming administration. (The New York Times) OpenAI is getting closer to launching an AI agent to automate your tasks AI agentsmodels that can do tasks for you on your behalfare all the rage. OpenAI is reportedly closer to releasing one, news that comes a few weeks after Anthropicannouncedits own. (Bloomberg) How this grassroots effort could make AI voices more diverse A massive volunteer-led effort to collect training data in more languages, from people of more ages and genders, could help make the next generation of voice AI more inclusive and less exploitative. (MIT Technology Review) Google DeepMind has a new way to look inside an AIs mind Autoencoders let us peer into the black box of artificial intelligence. They could help us create AI that is better understood and more easily controlled. (MIT Technology Review) Musk has expanded his legal assault on OpenAI to target Microsoft Musk has expanded his federal lawsuit against OpenAI, which alleges that the company has abandoned its nonprofit roots and obligations. Hes now going after Microsoft too, accusing it of antitrust violations in its work with OpenAI. (The Washington Post)

If youve ever been through a large US airport, youre probably at least vaguely aware of Clear. Maybe your interest (or irritation) has been piqued by the pods before the security checkpoints, the attendants in navy blue Its position in airports has made Clear Secure, with its roughly $3.75 billion market cap, the most visible biometric identity company in the United States. Over the past two decades, Clear has put more than 100 lanes in 58 airports across the US, and in the past decade it has entered 17 sports arenas and stadiums, from San Jose to Denver to Atlanta. Now you can also use its identity verification platform to rent tools at Home Depot, put your profile in front of recruiters on LinkedIn, and, as of this month, verify your identity as a rider on Uber. And soon enough, if Clear has its way, it may also be in your favorite retailer, bank, and even doctors officeor anywhere else that you currently have to pull out a wallet (or, of course, wait in line). The company that has helped millions of vetted members skip airport security lines is now working to expand its frictionless, face-first line-cutting service from the airport to just about everywhere, online and off, by promising to verify that you are who you say you are and you are where you are supposed to be. In doing so, CEO Caryn Seidman Becker told investors in an earnings call earlier this year, it has designs on being no less than the identity layer of the internet, as well as the universal identity platform of the physical world. All you have to do is show upand show your face. This is enabled by biometric technology, but Clear is far more than just a biometrics company. As Seidman Becker has told investors, biometrics arent the product they are a feature. Or, as she put it in a 2022 podcast interview, Clear is ultimately a platform company no different than Amazon or Applewith dreams, she added, of making experiences safer and easier, of giving people back their time, of giving people control, of using technology for frictionless experiences. (Clear did not make Seidman Becker available for an interview.) While the company has been building toward this sweeping vision for years, it now seems the time has finally come. A confluence of factors is currently accelerating the adoption ofeven necessity foridentity verification technologies: increasingly sophisticated fraud, supercharged by artificial intelligence that is making it harder to distinguish who or what is real; data breaches that seem to occur on a near daily basis; consumers who are more concerned about data privacy and security; and the lingering effects of the pandemics push toward contactless experiences. All of this is creating a new urgency around ways to verify information, especially our identitiesand, in turn, generating a massive opportunity for Clear. For years, Seidman Becker has been predicting that biometrics will go mainstream. But now that biometrics have, arguably, gone mainstream, whatand whobears the cost? Because convenience, even if chosen by only some of us, leaves all of us wrestling with the effects. Some critics warn that not everyone will benefit from a world where identity is routed through Clearmaybe because its too expensive, maybe because biometric technologies are often less effective at identifying people of color, people with disabilities, or those whose gender identity may not match what official documents say. Whats more, says Kaliya Young, an identity expert who has advised the US government, having a single private company disintermediating our biometric dataespecially facial datais the wrong architecture to manage identity. It seems they are trying to create a system like login with Google, but for everything in real life, Young warns. While the single sign-on option that Google (or Facebook or Apple) provides for websites and apps may make life easy, it also poses greater security and privacy risks by putting both our personal data and the keys to it in the hands of a single profit-driven entity: Were basically selling our identity soul to a private company, whos then going to be the gatekeeper everywhere one goes. Though Clear remains far less well known than Google, more than 27 million people have already helped it become that very gatekeeperand one of the largest private repositories of identities on the planet, as Nicholas Peddy, Clears chief technology officer, put it in an interview with MIT Technology Review this summer. With Clear well on the way to realizing its plan for a frictionless future, its time to try to understand both how we got here and what we have (been) signed up for. A new frontier in identity management Imagine this: On a Friday morning in the near future, you are rushing to get through your to-do list before a weekend trip to New York. In the morning, you apply for a new job on LinkedIn. During lunch, assured that recruiters are seeing your professional profile because its been verified by Clear, you pop out to Home Depot, confirm your identity with a selfie, and rent a power drill for a quick bathroom repair. Then, in the midafternoon, you drive to your doctors office; having already verified your identityprompted by a text message sent a few days earlieryou confirm your arrival with a selfie at a Clear kiosk.Before you go to bed, you plan your morning trip to the airport and set an alarmbut not too early, because you know that with Clear, you can quickly drop your bags and breeze through security. Once youre in New York, you head to Barclays Center, where youll be seeing your favorite singer; you skip the long queue out front to hop in the fast-track Clear line. Its late when the show is over, so you grab an Uber home and barely need to wait for a driver, who feels more comfortable thanks to your verified rider profile. At no point did you pull out your drivers license or fill out repetitive paperwork. All that was already on file. Everything was easy; everything was frictionless. More than 27 million people have already helped Clear become one of the largest private repositories of identities on the planet. This, at least, is the world that Clear is actively building toward. Part of Clears power, Seidman Becker often says, is that it can wholly replace our wallets: our credit cards, drivers licenses, health insurance cards, perhaps even building key fobs. But you cant just suddenly be all the cards you carry. For Clear to link your digital identity to your real-world self, you must first give up a bit of personal dataspecifically, your biometric data. Biometrics refers to the unique physical and behavioral characteristicsfaces, fingerprints, irises, voices, and gaits, among othersthat identify each of us as individuals. For better or worse, they typically remain stable during our lifetimes. Relying on biometrics for identification can be convenient, since people are apt to misplace a wallet or forget the answer to a security question. But on the other hand, if someone manages to compromise a database of biometric information, that convenience can become dangerous: We cannot easily change our face or fingerprint to secure our data again, the way we could change a compromised password. On a practical level, there are generally two ways that biometrics are used to identify individuals. The first, generally referred to one-to-many or one-to-n matching, compares one persons biometric identifier with a database full of them. This is sometimes associated with a stereotypical idea of dystopian surveillance in which real-time facial recognition from live video could allow authorities to identify anyone walking down the street. The other, one-to-one matching, is the basis for Clear; it compares a biometric identifier (like the face of a live person standing before an airport agent) with a previously recorded biometric template (such as a passport photo) to verify that they match. This is usually done with the individuals knowledge and consent, and it arguably poses a lower privacy risk. Often, one-to-one matching includes a layer of document verification, like checking that your passport is legitimate and matches a photograph you used to register with the system. The US Congress urgently saw the need for better identity management following the September 11 terrorist attacks; 18 of the 19 hijackers used fake identity documents to board their flights. In the aftermath, the newly created Transportation Security Administration (TSA) implemented security processes that slowed down air travel significantly. Part of the problem was that everybody was just treated the same at airports, recalls the serial media entrepreneur Steven Brillincluding, famously, former vice president Al Gore. It sounded awfully democratic but in terms of basic risk management and allocation of resources, it just didnt make any sense. Congress agreed, authorizing the TSA to create a program that would allow people who passed background checks to be recognized as trusted travelers and skip some of the scrutiny at the airport. In 2007, San Francisco's then-mayor, Gavin Newsom, had his irises scanned by Clear at the San Francisco International Airport.DAVID PAUL MORRIS/GETTY In 2003, Brill teamed up with Ajay Amlani, a technology entrepreneur and former adviser to the Department of Homeland Security, and founded a company called Verified Identity Pass (VIP) to provide biometric identity verification in the TSAs new program. The vision, says Amlani, was a unified fast lanesimilar to a toll lane. It appeared to be a win-win solution. The TSA had a private-sector partner for its registered-traveler program; VIP had a revenue stream from user fees; airports got a cut of the fees in exchange for leasing VIP space; By 2005, VIP had launched in its first airport, Orlando International in Florida. Membersinitially paying $80received Clear cards that contained a cryptographic representation of their fingerprint, iris scans, and a photo of their face taken at enrollment. They could use those cards at the airport to be escorted to the front of the security lines. The defense contracting giant Lockheed Martin, which already provided biometric capabilities to the US Department of Defense and the FBI, was responsible for deploying and providing technology for VIPs system, with additional technical expertise from Oracle and others. This left VIP to focus on marketing, pricing, branding, customer service, and consumer privacy policies," as the president of Lockheed Transportation and Security Solutions, Don Antonucci, said at the time. By 2009, nearly 200,000 people had joined. The company had received $116 million in investments and signed contracts with about 20 airports. It all seemed so promisingif VIP had not already inadvertently revealed the risks inherent in a system built on sensitive personal data. A lost laptop and a big opportunity From the beginning, there were concerns about the implications of VIPs Clear card for privacy, civil liberty, and equity, as well as questions about its effectiveness at actually stopping future terrorist attacks. Advocacy groups like the Electronic Privacy Information Center (EPIC) warned that the biometrics-based system would result in a surveillance infrastructure built on sensitive personal information, but data from the Pew Research Center shows that a majority of the public at the time felt that it was generally necessary to sacrifice some civil liberties in the name of safety. Then a security lapse sent the whole operation crumbling. In the summer of 2008, VIP reported that an unencrypted company laptop containing addresses, birthdays, and drivers license and passport numbers of 33,000 applicants had gone missing from an office at San Francisco International Airport (SFO)even though TSAs security protocol required it to encrypt all laptops holding personal data. NEIL WEBB The laptop was found about two weeks later and the company said no data was compromised. But it was still a mess for VIP. Months later, investors pushed Brill out, and associated costs led the company to declare bankruptcy and close the following year. Disgruntled users filed a class action lawsuit against VIP to recoup membership fees and punitive damages. Some users were upset they had recently renewed their subscriptions, and others worried about what would happen to their personal information. A judge temporarily prevented the company from selling user data, but the decision didnt hold. Seidman Becker and her longtime business partner Ken Cornick, both hedge fund managers, saw an opportunity. In 2010, they bought VIPand its user datain a bankruptcy sale for just under $6 million and registered a new company called Alclear. I was a big believer in biometrics, Seidman Becker told the tech journalists Kara Swisher and Lauren Goode in 2017. I wanted to build something that made the world a better place, and Clear was that platform. Initially, the new Clear followed closely in the footsteps of its predecessor: Lockheed Martin transferred the members information to the new company, which had acquired VIPs hardware and continued to use Clear cards to hold members biometrics. After the relaunch, Clear also started building partnerships with other companies in the travel industryincluding American Express, United Airlines, Alaska Airlines, Delta Airlines, and Hertz Rental Carsto bundle its service for free or at a discount. (Clear declined to specify how many of its users have such discounts, but in earnings calls the company has stressed its efforts to reduce the number of members paying reduced rates.) By 2014, improvements in internet latency and biometric processing speeds allowed Clear to eliminate the cards and migrate to a server-based systemwithout compromising data security, the company says. Clear emphasizes that it meets industry standards for keeping data secure, with methods including encryption, firewalls, and regular penetration testing by both internal and external teams. The company says it also maintains locked boxes around data relating to air travelers. Still, the reality is that every database of this kind is ultimately a target, and almost every day theres a massive breach or hack, says Chris Gilliard, a privacy and surveillance researcher who was recently named co-director of the Critical Internet Studies Institute. Over the years, even apparently well-protected biometric information has been compromised. Last year, for instance, a data breach at the genetic testing company 23andMe exposed sensitive informationincluding geographic locations, birth years, family trees, and user-uploaded photosfrom nearly 7 million customers. This is what Young, who helped facilitate the creation of the open-source identity management standards Open ID Connect and OAuth, means when she says that Clear has the wrong architecture for managing digital identity; its too much of a risk to keep our digital identities in a central database, cryptographically protected or not. She and many other identity and privacy experts believe that the most privacy-protecting way to manage digital identity is to use credentials, like a mobile drivers license, stored on peoples devices in digital wallets, she says. These digital credentials can have biometrics, but the biometrics in a central database are not being pinged for day to day use. But its not just data thats potentially vulnerable. In 2022 and 2023, Clear faced three high-profile security incidents in airports, including one in which a passenger successfully got through the companys checks using a boarding pass found in the trash. In another, a traveler in Alabama used someone elses ID to register for Clear and, later, to successfully pass initial security checks; he was discovered only when he tried to bring ammunition through a subsequent checkpoint. This spurred an investigation by the TSA, which turned up more alarming information: Nearly 50,000 photos used by Clear to enroll customers were flagged as non-matches by the companys facial recognition software. Some photos didnt even contain full faces, according to Bloomberg. (In a press release after the incident, the company refuted the reporting, describing it as a single human errorhaving nothing to do with our technology and stating that the images in question were not relied upon during the secure, multi-layered enrollment process.) How do you get to be the one? When I spoke to Brill this spring, he told me hed always envisioned that Clear would expand far beyond the airport. The idea I had was that once you had a trusted identity, you would potentially be able to use it for a lot of different things, he said, but the trick is to get something that is universally accepted. And thats the battle that Clear and anybody else has to fight, which is: How do you get to be the one? Goode Intelligence, a market research firm that focuses on the booming identity space, estimates that by 2029, there will be 1.5 billion digital identity wallets around the worldwith use for travel leading the way and generating an estimated $4.6 billion in revenue. Clear is just one player, and certainly not the biggest. ID.me, for instance, provides similar face-based identity verification and has over 130 million users, dwarfing Clears roughly 27 million. Its also already in use by numerous US federal and state agencies, including the IRS. The reality is that every database of this kind is ultimately a target, and almost every day theres a massive breach or hack. But as Goode Intelligence CEO Alan Goode tells me, Clears early-mover advantage, particularly in the US, puts it in a good space within North America [to] be more pervasiveor to become what Brill called the one that is most closely stitched into peoples daily lives. Clear began growing beyond travel in 2015, when it started offering biometric fast-pass access to what was then AT&T Park in San Francisco. Stadiums across California, Colorado, and Washington, and in major cities in other states, soon followed. Then came the pandemic, hitting Clear (and the entire travel industry) hard. But the crisis for Clears primary business actually accelerated its move into new spaces with Health Pass, which allowed organizations to confirm the health status of employees, residents, students, and visitors who sought access to a physical space. Users could upload vaccination cards to the Health Pass section in the Clear mobile app; the program was adopted by nearly 70 partners in 110 unique locations, including NFL stadiums, the Mariners T-Mobile Park, and the 9/11 Memorial Museum. Demand for vaccine verification eventually slowed, and Health Pass shut down in March 2024. But as Jason Sherwin, Clears senior director of health-care business development, said in a podcast interview earlier this year, it was the companys first foray into health carethe business line that currently represents its primary focus across everything were doing outside of the airport. Today, Clear kiosks for patient sign-ins are being piloted at Georgias Wellstar Health Systems, in conjunction with one of the largest providers of electronic health records in the United States: Epic (which is unrelated to the privacy nonprofit). Whats more, Health Pass enabled Clear to expand at a time when the survival of travel-focused businesses wasnt guaranteed. In November 2020, Clear had roughly 5 million members; today, that number has grown fivefold. The company went public in 2021 and has experienced double-digit revenue growth annually. These doctors office sign-ins, in which the system verifies patient identity via a selfie, rely on whats called Clear Verified, a platform the company has rolled out over the past several years that allows partners (health-care systems, as well as brick-and-mortar retailers, hotels, and online platforms) to integrate Clears identity checks into their own user-verification processes. It again seems like a win-win situation: Clear gets more users and a fee from companies using the platform, while companies confirm customers identity and information, and customers, in theory, get that valuable frictionless experience. One high-profile partnership, with LinkedIn, was announced last year: We know authenticity matters and we want the people, companies and jobs you engage with everyday to be real and trusted," Oscar Rodriguez, LinkedIns head of trust and privacy, said in a press release. All this comes together to create the foundation for what is Clears biggest advantage today: its network. The companys executives often speak about its embedded users across various services and platforms, as well as its ecosystem, meaning the venues where it is used. As Peddy explains, the value proposition for Clear today is not necessarily any particular technology or biometric algorithm, but how it all comes togetherand can work universally. Clear would be wherever our consumers need us to be, he saysit would sort of just be this ubiquitous thing that everybody has. Clear CEO Caryn Seidman Becker (left) rings the bell at the New York Stock Exchange in 2021.NYSE VIA TWITTER A prospectus to investors from the companys IPO makes the pitch simple: We believe Clear enables our partners to capture not just a greater share of their customers wallet, but a greater share of their overall lives. The more Clear is able to reach into customers lives, the more valuable customer data it can collect. All user interactions and experiences can be tracked, the companys privacy policy explains. While the policy states that Clear will not sell data and will never share biometric or health information without express consent, it also lays out the non-health and non-biometric data that it collects and can use for consumer research and marketing. This includes members demographic details, a record of every use of Clears various products, and even digital images and videos of the user. Documents obtained by OneZero offer some further detail into what Clear has at least considered doing with customer data: David Gershgorn writes about a 2015 presentation to representatives from Los Angeles International Airport, titled Identity DashboardValuable Marketing Data, which showed off what the company had collected, including the number of sports games users had attended and with whom, which credit cards they had, their favorite airlines and top destinations, and how often they flew first class or economy. Clear representatives emphasized to MIT Technology Review that the company does not share or sell information without consent, though they had nothing to add in response to a question about whether Clear can or does aggregate data to derive its own marketing insights, a business model popularized by Facebook. At Clear, privacy and security are job one, spokesperson Ricardo Quinto wrote in an email. We are opt-in. We never sell or share our members information and utilize a multilayered, best-in-class infosec system that meets the highest standards and compliance requirements. Nevertheless, this influx of customer data is not just good for business; its risky for customers. It creates another attack surface, Gilliard warns. This makes us less safe, not more, as a consistent identifier across your entire public and private life is the dream of every hacker, bad actor, and authoritarian. A face-based future for some Today, Clear is in the middle of another major change: replacing its use of iris scans and fingerprints with facial verification in airportspart of a TSA-required upgrade in identity verification, a TSA spokesperson wrote in an email to MIT Technology Review. For a long time, facial recognition technology for the highest security purposes was not ready for prime time, Seidman Becker told Swisher and Goode back in 2017. It wasnt operating with five nines, she addedthat is, 99.999% from a matching and an accuracy perspective. But today, facial recognition has significantly improved and the company has invested in enhancing image quality through improved capture, focus, and illumination, according to Quinto. The move is part of a broader shift toward facial recognition technology in US travel, bringing the country in line with practices at many international airports. The TSA began expanding facial identification from a few pilot programs this year, while airlines including Delta and United are also introducing face-based boarding, baggage drops, and even lounge access. And the International Air Transport Association, a trade group for the airline industry, is rolling out a contactless travel process that will allow passengers to check in, drop off their bags, and board their flightsall without showing either passports or tickets, just their faces. NEIL WEBB Privacy experts worry that relying on faces for identity verification is even riskier than other biometric methods. After all, its a lot easier to scan peoples faces passively than it is to scan irises or takefingerprints, Senator Jeff Merkley of Oregon, an outspoken critic of government surveillance and of the TSAs plans to employ facial verification at airports, said in an email. The point is that once a database of faces is built, it is potentially far more useful for surveillance purposes than, say, fingerprints. Everyone who values privacy, freedom, and civil rights should be concerned about the increasing, unchecked use of facial recognition technology by corporations and the federal government, Merkley wrote. Even if Clear is not in the business of surveillance today, it could, theoretically, pivot or go bankrupt and (again) sell off its parts, including user data. Jeramie Scott, senior counsel and director of the Project on Surveillance Oversight at EPIC, says that ultimately, the lack of federal [privacy] regulation means that were just taking the promises of companies like Clear at face value: Whatever they say about how they implement facial recognition today does not mean that thats how they'll be implementing facial recognition tomorrow. Making this particular scenario potentially more concerning is that the images stored by this private company are generally going to be much higher quality than those collected by scraping the internetwhich Albert Fox Cahn, the executive director of the Surveillance Technology Oversight Project (STOP), says would make its data far more useful for surveillance than that held by more controversial facial recognition companies like Clearview AI. Even a far less pessimistic read of Clears data collection reveals the challenges of using facial identification systems, whichas a 2019 report from the National Institute for Standards and Technology revealedhave been shown to work less effectively in certain populations, particularly people of African and East Asian descent, women, and elderly and very young people. NIST has also not tested identification accuracy for individuals who are transgender, but Gilliard says he expects the algorithms would fall short. More recent testing shows that some algorithms have improved, NIST spokesperson Chad Boutin tells MIT Technology Reviewthough accuracy is still short of the five nines that Seidman Becker once said Clear was aiming for. (Quinto, the Clear representative, maintains that Clears recent upgrades, combined with the fact that the companys testing involves comparing member photos to smaller galleries, rather than the millions used in NIST scenarios, means its technology remains accurate and suitable for secure environments like airports.) Even a very small error rate in a system that is deployed hundreds of thousands of times a day could still leave a lot of people at risk of misidentification, explains Hannah Quay-de La Vallee, a technologist at the Center for Democracy & Technology, a nonprofit based in Washington, DC. All this could make Clears services inaccessible to someeven if they can afford it, which is less likely given the recent increase in the subscription fee for travelers to $199 a year. The free Clear Verified Platform is already giving rise to access problems in at least one partnership, with LinkedIn. The professional networking site encourages users to verify their identities either with an employer email address or with Clear, which marketing materials say will yield more engagement. But some LinkedIn users have expressed concerns, claiming that even after uploading a selfie, they were unable to verify their identities with Clear if they were subscribed to a smaller phone company or if they had simply not had their phone number for enough time. As one Reddit user emphasized, Getting verified is a huge deal when getting a job. LinkedIn said it does not enable recruiters to filter, rank, or sort by whether a candidate has a verification badge, but also said that verified information does help people make more informed decisions as they build their network or apply for a job. Clear only said it works with our partners to provide them with the level of identity assurance that they require for their customers and referred us back to LinkedIn. An opt-in future that may not really be optional Maybe whats worse than waiting in line, or even being cut in front of, is finding yourself stuck in what turns out to be the wrong lineperhaps one that you never want to be in. That may be how it feels if you dont use Clear and similar biometric technologies. When I look at companies stuffing these technologies into vending machines, fast-food restaurants, schools, hospitals, and stadiums, what I see is resignation rather than acceptancepeople often dont have a choice, says Gilliard, the privacy and surveillance scholar. The life cycle of these things is that even when it is optional, oftentimes it is difficult to opt out. And while the stakes may seem relatively lowClear is, after all, a voluntary membership programthey will likely grow as the system is deployed more widely. As Seidman Becker said on Clears latest earnings call in early November, The lines between physical and digital interactions continue to blur. A verified identity isnt just a check mark. Its the foundation for everything we do in a high-stakes digital world. Consider a job ad posted by Clear earlier this year, seeking to hire a vice president for business development; it noted that the company has its eye on a number of additional sectors, including financial services, e-commerce, P2P networking, online trust, gaming, government, and more. Increasingly, companies and the government are making the submission of your biometrics a barrier to participation in society, Gilliard says. This will be particularly true at the airport, with the increasing ubiquity of facial recognition across all security checks and boarding processes, and where time-crunched travelers could be particularly vulnerable to Clears sales pitch. Airports have even privately expressed concerns about these scenarios to Clear. Correspondence from early 2022 between the company and staff at SFO, released in response to a public records request, reveals that the airport received a number of complaints about Clear staff improperly and deceitfully soliciting approaching passengers in the security checkpoint lanes outside of its premises, with an airport employee calling it completely unacceptable and aggressive and deceptive behavior. Of course, this isnt to say everyone with a Clear membership was coerced into signing up. Many people love it; the company told MIT Technology Review that it had a nearly 84% retention rate earlier this year. Still, for some experts, its worrisome to think that what Clear users are comfortable with ends up setting the ground rules for the rest of us. Were going to normalize potentially a bunch of biometric stuff but not have a sophisticated conversation about where and how were normalizing what, says Young. She worries this will empower actors who want to move toward a creepy surveillance state, or corporate surveillance capitalism on steroids. Without understanding what were building or how or where the guardrails are, she adds, I also worry that there could be major public backlash, and then legitimate uses [of biometric technology] are not understood and supported. But in the meantime, even superfans are grumbling about an uptick in wait times in the airports Clear lines. After all, if everyone decides to cut to the front of the line, that just creates a new long line of line-cutters.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How the largest gathering of US police chiefs is talking about AI James ODonnell The International Association of Chiefs of Police bills itself as the largest gathering of its type in the United States. Leaders from many of the countrys 18,000 police departments and even some from abroad convene for product demos, discussions, parties, and awards. I went along last month to see how artificial intelligence was being discussed, and the message to police chiefs seemed crystal clear: If your department is slow to adopt AI, fix that now. From the expo hall, talks, and interviews, it seems theyre already enthusiastically heeding the call. Read the full story. This story is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday. Roundtables: Whats Next for Mixed Reality: Glasses, Goggles, and More After years of trying, augmented-reality specs are at last a thing. If you want to learn more about where AR experiences are heading, join our editor-in-chief Mat Honan and AI hardware reporter James ODonnell for a Roundtables conversation streamed online at 2pm ET/11am PT today. Its for subscribers only but good news: this week our subscriptions are half price. Dont miss out! Read more about mixed reality: + We interviewed Palmer Luckey, founder of Oculus, about his plans to bring mixed-reality goggles to soldiers. Heres what he had to say. + The coolest thing about smart glasses is not the AR. Its the AI. + Snap has launched new augmented-reality Spectacles. Heres what we made of them. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 The FBI is investigating threats texted to Latino and LGBTQ+ people They claim recipients will be deported or sent to a re-education camp. (WP$)+ ICE can already sidestep sanctuary city laws through data-sharing centers. (Wired$)+Trump has confirmed he plans to use the military for mass deportations.(NYT$)2 Chinese tech groups are building AI teams in Silicon Valley Despite Washingtons best efforts to stymie their work. (FT$)+How a US ban on investing in Chinese startups could escalate under Trump.(Wired$)3 How Apple will cope with looming tariffsThe fact CEO Tim Cook already has a relationship with Trump will surely help. (Bloomberg$)4 Two undersea cables in the Baltic Sea have been disrupted It looks like Russia is trying to interfere with global undersea infrastructure. (CNN)+A Russian spy ship had to be escorted out of the Irish Sea last weekend too.(The Guardian)5 An AI tool could help solve math problems humans are stuck onIts a good example of how blending human and machine intelligence can produce positive results. (New Scientist$)+This AI system makes human tutors better at teaching children math. (MIT Technology Review) 6 Robots still struggle to match warehouse workers on some tasks For all the advances robots have made, picking things up and moving them around remains a big challenge. (NYT$)+AI is poised to automate todays most mundane manual warehouse task.(MIT Technology Review)7 Perplexitys AI search engine can now buy stuff for you How long until Google follows? (The Verge)8 Dozens of states are begging Congress to pass the kids online safety actIt has currently stalled in the House of Representatives due to censorship concerns. (The Verge)+Roblox is adding more controls to let parents set daily usage limits, block access to certain game genres, and more.(WSJ$)+ Why child safety bills are popping up all over the US9 The US Patent and Trademark Office banned staff from using generative AIIt cited security concerns plus the fact some tools exhibit bias, unpredictability, and malicious behavior. (Wired$)10 NASA might have killed life on MarsA new paper suggests that adding water to Martian soil might have been a bad move. (Quartz$)+ The ISS has been leaking air for 5 years, and engineers still cant agree why.(Ars Technica)Quote of the day We are bleeding cash as an industry. Thomas Laffont, co-founder of investment firm Coatue Management, says venture capital firms are struggling to make money amid a boom in AI investments, theWall Street Journalreports.The big story How mobile money supercharged Kenyas sports betting addiction BRIAN OTIENO April 2022 Mobile money has mostly been hugely beneficial for Kenyans. But it has also turbo-charged the countrys sports betting sector. Experts and public figures across the African continent are sounding the alarm over the growth of the sector increasingly loudly. Its produced tales of riches, but it has also broken families, consumed college tuitions, and even driven some to suicide. Read the full story. Jonathan W. Rosen We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + I just learned a pertinent word for this season:abscission. + Only some people will getthis but if you're one of them, youll enjoy it.+ Why Late of the Pier were one of the mostexciting UK bandsof the 2000s.+ Whether you call them crisps or chips, theyre goddamndelicious.

Recorded on November 19, 2024 Whats Next for Mixed Reality: Glasses, Goggles, and More. Speakers: Mat Honan, Editor in Chief, and James O'Donnell, AI hardware reporter. We are barreling toward the next big consumer device category: smart glasses. After years of trying, augmented-reality specs are at last a thing. Facebook recently showed off its Orion smart glasses, and Snap has introduced its second-generation pair. The Pentagon is also working on mixed-reality headsets that can be used on the battlefield. Hear fromMIT Technology Revieweditor in chief Mat Honan and AI hardware reporter James ODonnell for a conversation about where our AR experiences are heading. Related Coverage

You may have read thatit was a big week for Bluesky. If youre not familiar, Bluesky is, essentially, a Twitter clone that publishes short-form status updates. It gained more than 2 million users this week. On Wednesday,The Vergereportedit had crossed 15 million users. By Thursday, it was at 16 million. By Friday?17 million and counting. It was thenumber one appin Apples app store. Meanwhile, Threads, Metas answer to Twitter, put up even bigger numbers. The companys Adam Mosserireported that 15 million peoplehad signed up in November alone. Both apps are surging in usage. Many of these new users were seemingly fleeing X, the platform formerly known as Twitter. On the day after the election, more than115,000 people deactivated their X accounts, according to Similarweb data. Thats a step far past not logging on. It means giving up your username and social graph. Its nuking your account versus just ignoring it. Much of that migration is likely a reaction to Elon Musks support of Donald Trump, and his moves to elevate right-leaning content on the platform. Since Musk took over, X has reinstated a lot of previously banned accounts, very many of which are on the far right. It also tweaked its algorithm to make sure Musks own posts, which are often pro-Trump, get an extra level of promotion and prominence,according toKate Conger and Ryan Macs new bookCharacter Limit. There are two points I want to make here. The first is that tech and politics are just entirely enmeshed at this point. Thats due to the extreme extent to which tech has captured culture and the economy. Everything is a tech story now, including and especially politics. The second point is about what I see as a more long-term shift away from centralization. Whats more interesting to me than people fleeing a service because they dont like its politics is the emergence of unique experiences and cultures across all three of these services, as well as other, smaller competitors. Last year,we put Twitter killers on our list of 10 breakthrough technologies. But the breakthrough technology wasnt the rise of one service or the decline of another. It was decentralization. At the time, I wrote: Decentralized, or federated, social media allows for communication across independently hosted servers or platforms, using networking protocols such as ActivityPub, AT Protocol, or Nostr. It offers more granular moderation, more security against the whims of a corporate master or government censor, and the opportunity to control your social graph. Its even possible to move from one server to another and follow the same people. In the long run, massive, centralized social networks will prove to be an aberration. We are going to use different networks for different things. For example, Bluesky is great for breaking news because it does not deprioritize links and defaults to a social graph that shows updates from the people you follow in chronological order. (It also has a Discover feed and you can set up others for algorithmic discoverymore on that in a momentbut the default is the classic Twitter-esque timeline.) Threads, which has a more algorithmically defined experience, is great for surfacing interesting conversations from the past few days. I routinely find interesting comments and posts from two or three days before I logged on. At the same time, this makes it pretty lousy at any kind of real time experienceseemingly intentionallyand essentially hides that standard timeline of updates from people you follow in favor of an algorithmically-generated for you feed. Im going to go out on a limb here and say that while these are quite different, neither is inherently better. They offer distinct takes on product direction. And that ability to offer different experiences is a good thing. I think this is one area where Bluesky has a real advantage. Bluesky lets people bend the experience to their own will. You arent locked into the default following and discover experiences. You canroll your own custom feed, and follow custom feeds created by other people. (And Threads isnow testing something similar.) That customization means my experience on Bluesky may look nothing like yours. This is possible because Bluesky is a service running on top of the AT Protocol, an open protocol thats accessible to anyone and everyone. The entire idea is that social networking is too important for any one company or person to control it. So it is set up to allow anyone to run their own network using that protocol. And thats going to lead to a wide range of outcomes. Take moderation, as an example. The moderation philosophy of the AT Protocol is essentially that everyone is entitled to speech but not to reach. That means it isnt banning content at the protocol level, but that individual services can set up their own rules. Bluesky hasits own community guidelines. But those guidelines would not necessarily apply to other services running on the protocol. Furthermore, individuals can also moderate what types of posts they want to see. It lets peopleset up and choose different levels of what they want to allow. That, combined with the ability to roll your own feeds, combined with the ability of different services to run on top of the same protocol, sets up a very fragmented future. And thats just Bluesky. Theres also Nostr, which leans toward the crypto and tech crowds, at least for now. And Mastodon, which tends to have clusters of communities on various servers. All of them are growing. The era of the centralized, canonical feed is coming to an end. Whats coming next is going to be more dispersed, more fractured, more specialized. It will take place across these decentralized services, and also WhatsApp channels, Discord servers, and other smaller slices of Big Social. Thats going to be challenging. It will cause entirely new problems. But its also an incredible opportunity for individuals to take more control of their own experiences. If someone forwarded you this edition of The Debrief, you cansubscribe here. I appreciate your feedback on this newsletter. Drop me a line atmat.honan@technologyreview.comwith any and all thoughts. And of course, I love tips. Now read the rest of The Debrief The News TSMC halts advanced chip shipments for Chinese clients. It comes after some of its chips were found inside a Huawei AI processor. Google DeepMind has come up with a new way to peer inside AIs thought process. An AI lab out of Chicago is building tools to help creators prevent their work from being used in training data. Lina Khan may be on the way out, but shes going out with a bang: The FTC is preparing to investigate Microsofts cloud business. The Chat Every week Ill talk to one of MIT Technology Reviews reporters or editors to find out more about what theyve been working on. For today, I spoke with Casey Crownhart, senior climate reporter, about her coverage of the COP29 UN climate conference. Mat: COP29 is happening right now in Azerbaijan, do you have a sense of the mood? Casey: The vibes are weird in Baku this week, in part because of the US election. The US has been a strong leader in international climate talks in recent years, and an incoming Trump administration will certainly mean a big change. And the main goal of these talksreaching a climate finance agreementis a little daunting. Developing countries need something like $1 trillion dollars annually to cope with climate change. Thats a huge jump from the current target, so there are questions about how this agreement will shake out. Mat: Azerbaijan seems like a weird choice to host. I read one account from the conference saying you could smell the oil in the air. Why there? Casey: Azerbaijans economy is super reliant on fossil fuels, which definitely makes it an ironic spot for international climate negotiations. Theres a whole complicated process of picking the COP host each yearfive regions rotate hosting, and the countries in that region have to all agree on a pick when its their turn. Russia apparently vetoed most of the other choices in the Eastern European group this year, and the region settled on Azerbaijan as one of the only viable options. Mat: You write that if Trump pulls out of the UN Framework Convention on Climate Change, it would be like riding away on a rocket. Why would that be so much worse than dropping out of Paris? Casey: Trump withdrew from the Paris Agreement once already, and it was relatively easy for Biden to rejoin when he came into office. If, during his second term, Trump were to go a step further and pull out of the UNFCCC, its not just an agreement hes walking away from, its the whole negotiating framework. So the statement would be much bigger. Theres also the question of reversibility. Its not clear if Trump can actually withdraw from the UNFCCC on his own, and its also not clear what it would take to rejoin it. When the US joined in the 90s, the Senate had to agree, so getting back in might not be as simple as a future president signing something. Mat: What from COP29 are you optimistic about? Casey: Tough to find a glimmer of hope in all this, but if there is one, Id say Im optimistic that well see some countries step up, including the UK and China. The UK announced a new emissions target at the talks already, and itll be really interesting to see what role China plays at COP29 and moving forward. The Recommendation Once upon a time I was a gadget blogger. Its fun writing about gadgets! I miss it! Especially because at some point your phone became the only device you need. But! My beloved wife bought me a Whoop fitness tracker for my birthday. Its an always-on device that you wear around your wrist. Ive been Oura-curious for some time, but frankly I am a little bit terrified of rings. I spent a number of months going to a hand rehab clinic after a bike accident, and while I was there first learned about degloving and how commonly it happens to people because a ring gets caught on something. Just thought Id put that in your head too. Anyway! The whoop is a fabric bracelet with a little monitor on it. It tracks your movement, your heart rate, your sleep, and a lot more. Theres no screen, so its very low profile and unobtrusive. It is, however, pretty spendy: The device is free but the plan costs $239 annually.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. The rise of Bluesky, and the splintering of social You may have read that it was a big week for Bluesky. If youre not familiar, Bluesky is, essentially, a Twitter clone that publishes short-form status updates. Last Wednesday, The Verge reported it had crossed 15 million users. Its just ticked over 19 million now, and is the number one app in Apples app store. Meanwhile, Threads, Metas answer to Twitter, reportedly signed up 15 million people in November alone. Both apps are surging in usage. Many of these new users were seemingly fleeing X, the platform formerly known as Twitter, in reaction to Elon Musks support of Donald Trump, and his moves to elevate right-leaning content on the platform. But theres a deeper trend at play here. Were seeing a long-term shift away from massive centralized social networks. Read the full story. Mat Honan This story is from The Debrief, our newly-launched newsletter written by our editor-in-chief Mat Honan. Its his weekly take on the real stories behind the biggest news in techwith some links to stories we love and the occasional recommendation thrown in for good measure. Sign up to get it every Friday! Why the term women of childbearing age is problematic Jessica Hamzelou Every journalist has favorite topics. Mine include the quest to delay or reverse human aging, and new technologies for reproductive health and fertility. So when I saw trailers for The Substance, a film centered on one middle-aged womans attempt to reexperience youth, I had to watch it. I wont spoil the movie for anyone who hasnt seen it yet (although I should warn that it is not for the squeamish). But a key premise of the film involves harmful attitudes toward female aging. Hey, did you know that a womans fertility starts to decrease by the age of 25? a powerful male character asks early in the film. At 50, it just stops, he later adds. He never explains what stops, exactly, but to the viewer the message is pretty clear: If youre a woman, your worth is tied to your fertility. Once your fertile window is over, so are you. The insidious idea that womens bodies are, above all else, vessels for growing children has plenty of negative consequences for us all. But it also sets back scientific research and health policy. Read Jesss story to learn how. This story is from The Checkup, MIT Technology Reviews weekly biotech newsletter. Sign up to receive it in your inbox every Thursday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Trump plans to loosen US rules for self-driving cars No prizes for guessing who might be behind that idea. (Bloomberg$)+Elon Musk is ramping up his legal fight against OpenAI and Microsoft.(WSJ$)+Trump has appointed the FCCs Brendan Carr to lead the agency.(NPR)+Robotaxis are here. Its time to decide what to do about them. (MIT Technology Review)2 How Bluesky is handling its explosive growthIt has just 20 employees, and theyre working round the clock to deal with bugs, outages and moderation issues. (NYT$)+Just joined Bluesky? Heres how to use it.(The Verge)+How to fix the internet.(MIT Technology Review) 3 Biden agreed to some small but significant AI limits with Xi Jinping I think we can all get behind the idea that nuclear weapons should be exclusively controlled by humans. (Politico)+Biden has lifted a ban on Ukraine using long-raise missiles to strike inside Russia.(BBC)4 Big Tech is trying to sink the US online child safety billAnd, as it stands, its lobbying efforts look very likely to succeed. (WSJ$)5 Amazon has launched a rival to Temu and Shein Nothing on Haul costs more than $20. (BBC)+Welcome to the slop era of online shopping. (The Atlantic$)6 The Mike Tyson-Jake Paul fight on Netflix was plagued by glitchesDespite that, 60 million households still tuned in. (Deadline)7 AI models can work together faster in their own languageLinking different models together could help tackle thorny problems individual ones cant solve. (New Scientist$)8 Tech companies are training their AI on movie subtitlesA database called OpenSubtitles provides a rare glimpse into what goes into these systems. (The Atlantic$)9 McDonalds is trying to bring back NFTsRemember those? (Gizmodo)10 A lot of people are confusing Starlink satellites with UFOs Guess itll take us a while for us to get used to seeing them. (Ars Technica)Quote of the day F*** you, Elon Musk. Brazils first lady, Janja Lula da Silva, makes her views clear during a speech calling for tougher social media regulation ahead of the G20 summit in Rio de Janeiro,Reutersreports.The big story Alina Chan tweeted life into the idea that the virus came from a lab COURTESY PHOTO June 2021 Alina Chan started asking questions in March 2020. She was chatting with friends on Facebook about the virus then spreading out of China. She thought it was strange that no one had found any infected animal. She wondered why no one was admitting another possibility, which to her seemed very obvious: the outbreak might have been due to a lab accident.Chan is a postdoc in a gene therapy lab at the Broad Institute, a prestigious research institute affiliated with both Harvard and MIT. Throughout 2020, Chan relentlessly stoked scientific argument, and wasnt afraid to pit her brain against the best virologists in the world. Her persistence even helped change some researchers minds.Read the full story.Antonio Regalado We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + WhyQuincy Joneswas the best of the best. + Thesehandy appsare a great way to save articles to read later on (Pocket is my own personal favorite.)+ How to resurrect aghost riverin the Bronx.+ Look after yourstainless steel pans, and your stainless steel pans will look after you.

AI has led to breakthroughs in drug discovery and robotics and is in the process of entirely revolutionizing how we interact with machines and the web. The only problem is we dont know exactly how it works, or why it works so well. We have a fair idea, but the details are too complex to unpick. Thats a problem: It could lead us to deploy an AI system in a highly sensitive field like medicine without understanding that it could have critical flaws embedded in its workings. A team at Google DeepMind that studies something called mechanistic interpretability has been working on new ways to let us peer under the hood. At the end of July, it released Gemma Scope, a tool to help researchers understand what is happening when AI is generating an output. The hope is that if we have a better understanding of what is happening inside an AI model, well be able to control its outputs more effectively, leading to better AI systems in the future. I want to be able to look inside a model and see if its being deceptive, says Neel Nanda, who runs the mechanistic interpretability team at Google DeepMind. It seems like being able to read a models mind should help. Mechanistic interpretability, also known as mech interp, is a new research field that aims to understand how neural networks actually work. At the moment, very basically, we put inputs into a model in the form of a lot of data, and then we get a bunch of model weights at the end of training. These are the parameters that determine how a model makes decisions. We have some idea of whats happening between the inputs and the model weights: Essentially, the AI is finding patterns in the data and making conclusions from those patterns, but these patterns can be incredibly complex and often very hard for humans to interpret. Its like a teacher reviewing the answers to a complex math problem on a test. The studentthe AI, in this casewrote down the correct answer, but the work looks like a bunch of squiggly lines. This example assumes the AI is always getting the correct answer, but thats not always true; the AI student may have found an irrelevant pattern that its assuming is valid. For example, some current AI systems will give you the result that 9.11 is bigger than 9.8. Different methods developed in the field of mechanistic interpretability are beginning to shed a little bit of light on what may be happening, essentially making sense of the squiggly lines. A key goal of mechanistic interpretability is trying to reverse-engineer the algorithms inside these systems, says Nanda. We give the model a prompt, like Write a poem, and then it writes some rhyming lines. What is the algorithm by which it did this? Wed love to understand it. To find featuresor categories of data that represent a larger conceptin its AI model, Gemma, DeepMind ran a tool known as a sparse autoencoder on each of its layers. You can think of a sparse autoencoder as a microscope that zooms in on those layers and lets you look at their details. For example, if you prompt Gemma about a chihuahua, it will trigger the dogs feature, lighting up what the model knows about dogs. The reason it is considered sparse is that its limiting the number of neurons used, basically pushing for a more efficient and generalized representation of the data. The tricky part of sparse autoencoders is deciding how granular you want to get. Think again about the microscope. You can magnify something to an extreme degree, but it may make what youre looking at impossible for a human to interpret. But if you zoom too far out, you may be limiting what interesting things you can see and discover. DeepMinds solution was to run sparse autoencoders of different sizes, varying the number of features they want the autoencoder to find. The goal was not for DeepMinds researchers to thoroughly analyze the results on their own. Gemma and the autoencoders are open-source, so this project was aimed more at spurring interested researchers to look at what the sparse autoencoders found and hopefully make new insights into the model's internal logic. Since DeepMind ran autoencoders on each layer of their model, a researcher could map the progression from input to output to a degree we havent seen before. This is really exciting for interpretability researchers, says Josh Batson, a researcher at Anthropic. If you have this model that youve open-sourced for people to study, it means that a bunch of interpretability research can now be done on the back of those sparse autoencoders. It lowers the barrier to entry to people learning from these methods. Neuronpedia, a platform for mechanistic interpretability, partnered with DeepMind in July to build a demo of Gemma Scope that you can play around with right now. In the demo, you can test out different prompts and see how the model breaks up your prompt and what activations your prompt lights up. You can also mess around with the model. For example, if you turn the feature about dogs way up and then ask the model a question about US presidents, Gemma will find some way to weave in random babble about dogs, or the model may just start barking at you. One interesting thing about sparse autoencoders is that they are unsupervised, meaning they find features on their own. That leads to surprising discoveries about how the models break down human concepts. My personal favorite feature is the cringe feature, says Joseph Bloom, science lead at Neuronpedia. It seems to appear in negative criticism of text and movies. Its just a great example of tracking things that are so human on some level. You can search for concepts on Neuronpedia and it will highlight what features are being activated on specific tokens, or words, and how strongly each one is activated. If you read the text and you see whats highlighted in green, thats when the model thinks the cringe concept is most relevant. The most active example for cringe is somebody preaching at someone else, says Bloom. Some features are proving easier to track than others. One of the most important features that you would want to find for a model is deception, says Johnny Lin, founder of Neuronpedia. Its not super easy to find: Oh, theres the feature that fires when its lying to us. From what Ive seen, it hasnt been the case that we can find deception and ban it. DeepMinds research is similar to what another AI company, Anthropic, did back in May with Golden Gate Claude. It used sparse autoencoders to find the parts of Claude, their model, that lit up when discussing the Golden Gate Bridge in San Francisco. It then amplified the activations related to the bridge to the point where Claude literally identified not as Claude, an AI model, but as the physical Golden Gate Bridge and would respond to prompts as the bridge. Although it may just seem quirky, mechanistic interpretability research may prove incredibly useful. As a tool for understanding how the model generalizes and what level of abstraction its working at, these features are really helpful, says Batson. For example, a team lead by Samuel Marks, now at Anthropic, used sparse autoencoders to find features that showed a particular model was associating certain professions with a specific gender. They then turned off these gender features to reduce bias in the model. This experiment was done on a very small model, so its unclear if the work will apply to a much larger model. Mechanistic interpretability research can also give us insights into why AI makes errors. In the case of the assertion that 9.11 is larger than 9.8, researchers from Transluce saw that the question was triggering the parts of an AI model related to Bible verses and September 11. The researchers concluded the AI could be interpreting the numbers as dates, asserting the later date, 9/11, as greater than 9/8. And in a lot of books like religious texts, section 9.11 comes after section 9.8, which may be why the AI thinks of it as greater. Once they knew why the AI made this error, the researchers tuned down the AI's activations on Bible verses and September 11, which led to the model giving the correct answer when prompted again on whether 9.11 is larger than 9.8. There are also other potential applications. Currently, a system-level prompt is built into LLMs to deal with situations like users who ask how to build a bomb. When you ask ChatGPT a question, the model is first secretly prompted by OpenAI to refrain from telling you how to make bombs or do other nefarious things. But its easy for users to jailbreak AI models with clever prompts, bypassing any restrictions. If the creators of the models are able to see where in an AI the bomb-building knowledge is, they can theoretically turn off those nodes permanently. Then even the most cleverly written prompt wouldnt elicit an answer about how to build a bomb, because the AI would literally have no information about how to build a bomb in its system. This type of granularity and precise control are easy to imagine but extremely hard to achieve with the current state of mechanistic interpretability. A limitation is the steering [influencing a model by adjusting its parameters] is just not working that well, and so when you steer to reduce violence in a model, it ends up completely lobotomizing its knowledge in martial arts. Theres a lot of refinement to be done in steering, says Lin. The knowledge of bomb making, for example, isnt just a simple on-and-off switch in an AI model. It most likely is woven into multiple parts of the model, and turning it off would probably involve hampering the AIs knowledge of chemistry. Any tinkering may have benefits but also significant trade-offs. That said, if we are able to dig deeper and peer more clearly into the mind of AI, DeepMind and others are hopeful that mechanistic interpretability could represent a plausible path to alignmentthe process of making sure AI is actually doing what we want it to do.

We are on the cusp of a voice AI boom, with tech companies such as Apple and OpenAI rolling out the next generation of artificial-intelligence-powered assistants. But the default voices for these assistants are often white AmericanBritish, if youre luckyand most definitely speak English. They represent only a tiny proportion of the many dialects and accents in the English language, which spans many regions and cultures. And if youre one of the billions of people who dont speak English, bad luck: These tools dont sound nearly as good in other languages. This is because the data that has gone into training these models is limited. In AI research, most data used to train models is extracted from the English-language internet, which reflects Anglo-American culture. But there is a massive grassroots effort underway to change this status quo and bring more transparency and diversity to what AI sounds like: Mozillas Common Voice initiative. The data set Common Voice has created over the past seven years is one of the most useful resources for people wanting to build voice AI. It has seen a massive spike in downloads, partly thanks to the current AI boom; it recently hit the 5 million mark, up from 38,500 in 2020. Creating this data set has not been easy, mainly because the data collection relies on an army of volunteers. Their numbers have also jumped, from just under 500,000 in 2020 to over 900,000 in 2024. But by giving its data away, some members of this community argue, Mozilla is encouraging volunteers to effectively do free labor for Big Tech. Since 2017, volunteers for the Common Voice project have collected a total of 31,000 hours of voice data in around 180 languages as diverse as Russian, Catalan, and Marathi. If youve used a service that uses audio AI, its likely been trained at least partly on Common Voice. Mozillas cause is a noble one. As AI is integrated increasingly into our lives and the ways we communicate, it becomes more important that the tools we interact with sound like us. The technology could break down communication barriers and help convey information in a compelling way to, for example, people who cant read. But instead, an intense focus on English risks entrenching a new colonial world order and wiping out languages entirely. It would be such an own goal if, rather than finally creating truly multimodal, multilingual, high-performance translation models and making a more multilingual world, we actually ended up forcing everybody to operate in, like, English or French, says EM Lewis-Jong, a director for Common Voice. Common Voice is open source, which means anyone can see what has gone into the data set, and users can do whatever they want with it for free. This kind of transparency is unusual in AI data governance. Most large audio data sets simply arent publicly available, and many consist of data that has been scraped from sites like YouTube, according to research conducted by a team from the University of Washington, and Carnegie Mellon andNorthwestern universities. The vast majority of language data is collected by volunteers such as Blent zden, a researcher from Turkey. Since 2020, he has been not only donating his voice but also raising awareness around the project to get more people to donate. He recently spent two full-time months correcting data and checking for typos in Turkish. For him, improving AI models is not the only motivation to do this work. Im doing it to preserve cultures, especially low-resource [languages], zden says. He tells me he has recently started collecting samples of Turkeys smaller languages, such as Circassian and Zaza. However, as I dug into the data set, I noticed that the coverage of languages and accents is very uneven. There are only 22 hours of Finnish voices from 231 people. In comparison, the data set contains 3,554 hours of English from 94,665 speakers. Some languages, such as Korean and Punjabi, are even less well represented. Even though they have tens of millions of speakers, they account for only a couple of hours of recorded data. This imbalance has emerged because data collection efforts are started from the bottom up by language communities themselves, says Lewis-Jong. Were trying to give communities what they need to create their own AI training data sets. We have a particular focus on doing this for language communities where there isnt any data, or where maybe larger tech organizations might not be that interested in creating those data sets, Lewis-Jong says. They hope that with the help of volunteers and various bits of grant funding, the Common Voice data set will have close to 200 languages by the end of the year. Common Voices permissive license means that many companies rely on itfor example, the Swedish startup Mabel AI, which builds translation tools for health-care providers. One of the first languages the company used was Ukrainian; it built a translation tool to help Ukrainian refugees interact with Swedish social services, says Karolina Sjberg, Mabel AIs founder and CEO. The team has since expanded to other languages, such as Arabic and Russian. The problem with a lot of other audio data is that it consists of people reading from books or texts. The result is very different from how people really speak, especially when they are distressed or in pain, Sjberg says. Because anyone can submit sentences to Common Voice for others to read aloud, Mozillas data set also includes sentences that are more colloquial and feel more natural, she says. Not that it is perfectly representative. The Mabel AI team soon found out that most voice data in the languages it needed was donated by younger men, which is fairly typical for the data set. The refugees that we intended to use the app with were really anything but younger men, Sjberg says. So that meant that the voice data that we needed did not quite match the voice data that we had. The team started collecting its own voice data from Ukrainian women, as well as from elderly people. Unlike other data sets, Common Voice asks participants to share their gender and details about their accent. Making sure different genders are represented is important to fight bias in AI models, says Rebecca Ryakitimbo, a Common Voice fellow who created the project's gender action plan. More diversity leads not only to better representation but also to better models. Systems that are trained on narrow and homogenous data tend to spew stereotyped and harmful results. We dont want a case where we have a chatbot that is named after a woman but does not give the same response to a woman as it would a man, she says. Ryakitimbo has collected voice data in Kiswahili in Tanzania, Kenya, and the Democratic Republic of Congo. She tells me she wanted to collect voices from a socioeconomically diverse set of Kiswahili speakers and has reached out to women young and old living in rural areas, who might not always be literate or even have access to devices. This kind of data collection is challenging. The importance of collecting AI voice data can feel abstract to many people, especially if they arent familiar with the technologies. Ryakitimbo and volunteers would approach women in settings where they felt safe to begin with, such as presentations on menstrual hygiene, and explain how the technology could, for example, help disseminate information about menstruation. For women who did not know how to read, the team read out sentences that they would repeat for the recording. The Common Voice project is bolstered by the belief that languages form a really important part of identity. We think its not just about language, but about transmitting culture and heritage and treasuring peoples particular cultural context, says Lewis-Jong. There are all kinds of idioms and cultural catchphrases that just dont translate, they add. Common Voice is the only audio data set where English doesnt dominate, says Willie Agnew, a researcher at Carnegie Mellon University who has studied audio data sets. Im very impressed with how well they've done that and how well they've made this data set that is actually pretty diverse, Agnew says. It feels like theyre way far ahead of almost all the other projects we looked at. I spent some time verifying the recordings of other Finnish speakers on the Common Voice platform. As their voices echoed in my study, I felt surprisingly touched. We had all gathered around the same cause: making AI data more inclusive, and making sure our culture and language was properly represented in the next generation of AI tools. But I had some big questions about what would happen to my voice if I donated it. Once it was in the data set, I would have no control about how it might be used afterwards. The tech sector isnt exactly known for giving people proper credit, and the data is available for anyones use. As much as we want it to benefit the local communities, theres a possibility that also Big Tech could make use of the same data and build something that then comes out as the commercial product, says Ryakitimbo. Though Mozilla does not share who has downloaded Common Voice, Lewis-Jong tells me Meta and Nvidia have said that they have used it. Open access to this hard-won and rare language data is not something all minority groups want, says Harry H. Jiang, a researcher at Carnegie Mellon University, who was part of the team doing audit research. For example, Indigenous groups have raised concerns. Extractivism is something that Mozilla has been thinking about a lot over the past 18 months, says Lewis-Jong. Later this year the project will work with communities to pilot alternative licenses including Nwulite Obodo Open Data License, which was created by researchers at the University of Pretoria for sharing African data sets more equitably. For example, people who want to download the data might be asked to write a request with details on how they plan to use it, and they might be allowed to license it only for certain products or for a limited time. Users might also be asked to contribute to community projects that support poverty reduction, says Lewis-Jong. Lewis-Jong says the pilot is a learning exercise to explore whether people will want data with alternative licenses, and whether they are sustainable for communities managing them. The hope is that it could lead to something resembling open source 2.0. In the end, I decided to donate my voice. I received a list of phrases to say, sat in front of my computer, and hit Record. One day, I hope, my effort will help a company or researcher build voice AI that sounds less generic, and more like me. This story has been updated.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How this grassroots effort could make AI voices more diverse We are on the cusp of a voice AI boom, as tech companies roll out the next generation of artificial-intelligence-powered assistants. But the default voices for these assistants are often white AmericanBritish, if youre luckyand most definitely speak English. And if youre one of the billions of people who dont speak English, bad luck: These tools dont sound nearly as good in other languages. This is because the data that has gone into training these models is limited. In AI research, most data used to train models is extracted from the English-language internet, which reflects Anglo-American culture. But there is a massive grassroots effort underway to change this status quo and bring more transparency and diversity to what AI sounds like. Read the full story. Melissa Heikkil Azalea: a science-fiction story Fancy something fiction to read this weekend? If you enjoy Sci-Fi, check out this story written by Paolo Bacigalupi, featured in the latest edition of our print magazine. It imagines a future shaped by climate changeread it for yourself here. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Cruise has admitted to falsifying a crash report The report failed to mention that its robotaxi dragged a pedestrian after striking her. (San Francisco Chronicle)+ The firm has been fined $500,000 to resolve the criminal charges. (WP $)2 The US plans to investigate Microsofts cloud business As the Biden administration prepares to hand over power to Donald Trumps team. (FT $)3 Silicon Valley hates regulation. So does Trump. AI and energy ventures could be the first to prosper under lighter-touch governance. (WP $)+ Peter Thiel claims the tech industry is fed up with wokeness. (Insider $)4 Elon Musks cost-cutting team will be working 80+ hours a week And youll need to subscribe to X to apply. (WSJ $)+ As if that wasnt appealing enough, the positions are also unpaid. (NBC News)+ The lucky workers can expect a whole lot of meetings. (Bloomberg $)5 The trolls are in charge now And its increasingly unclear whats a joke and whats an actual threat. (The Atlantic $)+ Its possible, but not guaranteed, that Trumps more controversial cabinet picks will be defeated in the Senate. (New Yorker $)6 How to keep abortion plans private in the age of TrumpReproductive rights are under threat. Heres how to protect them. (The Markup) 7 The first mechanical Qubit is here And mechanical quantum computers could be the first to benefit. (IEEE Spectrum)+ Quantum computing is taking on its biggest challenge: noise. (MIT Technology Review) 8 Can Bluesky recapture the old Twitters magic?No algorithms, no interfering billionaires. (Vox) + More than one million new users joined the platform earlier this week. (TechCrunch)9 Weight-loss drugs could help to treat chronic pain And could present a safer alternative to opioids. (New Scientist $)+ Weight-loss injections have taken over the internet. But what does this mean for people IRL? (MIT Technology Review)10 These are the most expensive photographs ever taken The first human-taken pictures from space are truly awe-inspiring. (The Guardian)Quote of the day It feels like its a platform for and by real people. US politician Alexandria Ocasio-Cortez tells the Washington Post about the appeal of Bluesky as users join the social network after abandoning X. The big story How environmental DNA is giving scientists a new way to understand our world February 2024 Environmental DNA is a relatively inexpensive, widespread, potentially automated way to observe the diversity and distribution of life.Unlike previous techniques, which could identify DNA from, say, a single organism, the method also collects the swirling cloud of other genetic material that surrounds it. It can serve as a surveillance tool, offering researchers a means of detecting the seemingly undetectable.By sampling eDNA, or mixtures of genetic material in water, soil, ice cores, cotton swabs, or practically any environment imaginable, even thin air, it is now possible to search for a specific organism or assemble a snapshot of all the organisms in a given place.It offers a thrilling and potentially chilling way to collect information about organisms, including humans, as they go about their everyday business. Read the full story.Peter Andrey Smith We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Smells like punk spirit. + If youve been feeling creaky lately (and who hasnt), give these mobility exercises a go.+ Talk about a glow upthese beautiful locations really do emanate light.+ Its the truly chilling collab we never knew we needed: Bon Jovi has joined forces with Mr Worldwide himself, Pitbull.

This article first appeared in The Checkup,MIT Technology Reviewsweekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,sign up here. Every journalist has favorite topics. Regular Checkup readers might already know some of mine, which include the quest to delay or reverse human aging, and new technologies for reproductive health and fertility. So when I saw trailers for The Substance, a film centered on one middle-aged womans attempt to reexperience youth, I had to watch it. I wont spoil the movie for anyone who hasnt seen it yet (although I should warn that it is not for the squeamish, or anyone with an aversion to gratuitous close-ups of bums and nipples). But a key premise of the film involves harmful attitudes toward female aging. Hey, did you know that a womans fertility starts to decrease by the age of 25? a powerful male character asks early in the film. At 50, it just stops, he later adds. He never explains what stops, exactly, but to the viewer the message is pretty clear: If youre a woman, your worth is tied to your fertility. Once your fertile window is over, so are you. The insidious idea that womens bodies are, above all else, vessels for growing children has plenty of negative consequences for us all. But it has also set back scientific research and health policy. Earlier this week, I chatted about this with Alana Cattapan, a political scientist at the University of Waterloo in Ontario, Canada. Cattapan has been exploring the concept of women of reproductive agea descriptor that is ubiquitous in health research and policy. The idea for the research project came to her when the Zika virus was making headlines around eight years ago. I was planning on going to the Caribbean for a trip related to my partners research, and I kept getting advice that women of reproductive age shouldnt go, she told me. At the time, Zika was being linked to microcephalyunusually small headsin newborn babies. It was thought that the virus was affecting key stages of fetal development. Cattapan wasnt pregnant. And she wasnt planning on becoming pregnant at the time. So why was she being advised to stay away from areas with the virus? The experience got her thinking about the ways in which attitudes toward our bodies are governed by the idea of potential pregnancy. Take, for example, biomedical research on the causes and treatment of disease. Womens health has lagged behind mens as a focus of such work, for multiple reasons. Male bodies have long been considered the default human form, for example. And clinical trials have historically been designed in ways that make them less accessible for women. Fears about the potential effects of drugs on fetuses have also played a significant role in keeping people who have the potential to become pregnant out of studies. Scientific research has excluded women of reproductive age, or women who might potentially conceive, in a blanket way, says Cattapan. The research that we have on many, many drugs does not include women and certainly doesnt include women in pregnancy. This lack of research goes some way to explaining why women are much more likely to experience side effects from drugssome of them fatal. Over the last couple of decades, greater effort has been made to include people with ovaries and uteruses in clinical research. But we still have a long way to go. Women are also often subjected to medical advice designed to protect a potential fetus, whether they are pregnant or not. Official guidelines on how much mercury-containing fish it is safe to eat can be different for women of childbearing age, according to the US Environmental Protection Agency, for example. And in 2021, the World Health Organization used the same language to describe people who should be a focus of policies to reduce alcohol consumption. The takeaway message is that its women who should be thinking about fetal health, says Cattapan. Not the industries producing these chemicals or the agencies that regulate them. Not even the men who contribute to a pregnancy. Just women who stand a chance of getting pregnant, whether they intend to or not. It puts the onus of the health of future generations squarely on the shoulders of women, she says. Another problem is the language itself. The term women of reproductive age typically includes women between 15 and 44. Women at one end of that spectrum will have very different bodies and a very different set of health risks from those at the other. And the term doesnt account for people who might be able to get pregnant but dont necessarily identify as female. In other cases it is overly broad. In the context of the Zika virus, for example, it was not all women between the ages of 15 and 44 who should have considered taking precautions. The travel advice didnt apply to people whod had hysterectomies or did not have sex with men, for example, says Cattapan. Precision here matters, she says. More nuanced health advice would be helpful in cases like these. Guidelines often read as though theyre written for people assumed to be stupid, she adds. I dont think that needs to be the case. Another thing On Thursday, president-elect Donald Trump said that he will nominate Robert F. Kennedy Jr. to lead the US Department of Health and Human Services. The news was not entirely a surprise, given that Trump had told an audience at a campaign rally that he would let Kennedy go wild on health, the foods, and the medicines. The role would give Kennedy some control over multiple agencies, including the Food and Drug Administration, which regulates medicines in the US, and the Centers for Disease Control and Prevention, which coordinates public health advice and programs. Thats extremely concerning to scientists, doctors, and health researchers, given Kennedys positions on evidence-based medicine, including his antivaccine stance. A few weeks ago, in a post on X, he referred to the FDAs aggressive suppression of psychedelics, peptides, stem cells, raw milk, hyperbaric therapies, chelating compounds, ivermectin, hydroxychloroquine, vitamins, clean foods, sunshine, exercise, nutraceuticals and anything else that advances human health and cant be patented by Pharma. If you work for the FDA and are part of this corrupt system, I have two messages for you, continued the post. 1. Preserve your records, and 2. Pack your bags. Theres a lot to unpack here. But briefly, we dont yet have good evidence that mind-altering psychedelic drugs are the mental-health cure-alls some claim they are. Theres not enough evidence to support the many unapproved stem-cell treatments sold by clinics throughout the US and beyond, either. These treatments can be dangerous. Health agencies are currently warning against the consumption of raw unpasteurized milk, because it might carry the bird flu virus that has been circulating in US dairy farms. And its far too simplistic to lump all vitamins togethersome might be of benefit to some people, but not everyone needs supplements, and high doses can be harmful. Kennedys 2021 book The Real Anthony Fauci has already helped spread misinformation about AIDS. Here at MIT Technology Review, well continue our work reporting on whatever comes next. Watch this space. Now read the rest of The Checkup Read more from MIT Technology Reviews archive The tech industry has a gender problem, as the Gamergate and various #MeToo scandals made clear. A new generation of activists is hoping to remedy it. Male and female immune systems work differently. Which is another reason why its vital to study both women and female animals as well as males. Both of the above articles were published in the Gender issue of MIT Technology Review magazine. You can read more from that issue online here. Women are more likely to receive abuse online. My colleague Charlotte Jee spoke to the technologists working on an alternative way to interact online: a feminist internet. From around the web The scientific community and biopharma investors are reacting to the news of Robert F. Kennedy Jr.s nomination to lead the Department of Health and Human Services. Its hard to see HHS functioning, said one biotech analyst. (STAT) Virologist Beata Halassy successfully treated her own breast cancer with viruses she grew in the lab. She has no regrets. (Nature) Could diet influence the growth of endometriosis lesions? Potentially, according to research in mice fed high-fat, low-fiber Western diets. (BMC Medicine) Last week, 43 female rhesus macaque monkeys escaped from a lab in South Carolina. The animals may have a legal claim to freedom. (Vox)

This article is from The Spark, MIT Technology Reviews weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. Its time for a partythe Conference of the Parties, that is. Talks kicked off this week at COP29 in Baku, Azerbaijan. Running for a couple of weeks each year, the global summit is the largest annual meeting on climate change. The issue on the table this time around: Countries need to agree to set a new goal on how much money should go to developing countries to help them finance the fight against climate change. Complicating things? A US president-elect whose approach to climate is very different from that of the current administration (understatement of the century). This is a big moment that could set the tone for what the next few years of the international climate world looks like. Heres what you need to know about COP29 and how Donald Trumps election is coloring things. The UN COP meetings are an annual chance for nearly 200 nations to get together to discuss (and hopefully act on) climate change. Greatest hits from the talks include the Paris Agreement, a 2015 global accord that set a goal to limit global warming to 1.5 C (2.7 F) above preindustrial levels. This year, the talks are in Azerbaijan, a petrostate if there ever was one. Oil and gas production makes up over 90% of the countrys export revenue and nearly half its GDP as of 2022. A perfectly ironic spot for a global climate summit! The biggest discussion this year centers on global climate financespecifically, how much of it is needed to help developing countries address climate change and adapt to changing conditions. The current goal, set in 2009, is for industrialized countries to provide $100 billion each year to developing nations. The deadline was 2020, and that target was actually met for the first time in 2022, according to the Organization for Economic Cooperation and Development, which keeps track of total finance via reports from contributing countries. Currently, most of that funding is in the form of public loans and grants. The thing is, that $100 billion number was somewhat arbitraryin Paris in 2015, countries agreed that a new, larger target should be set in 2025 to take into account how much countries actually need. Its looking as if the magic number is somewhere around $1 trillion each year. However, it remains to be seen how this goal will end up shaking out, because there are disagreements about basically every part of this. What should the final number be? What kind of money should countjust public funds, or private investments as well? Which nations should pay? How long will this target stand? What, exactly, would this money be going toward? Working out all those details is why nations are gathering right now. But one shadow looming over these negotiations is the impending return of Donald Trump. As I covered last week, Trumps election will almost certainly result in less progress on cutting emissions than we might have seen under a more climate-focused administration. But arguably an even bigger deal than domestic progress (or lack thereof) will be how Trump shifts the countrys climate position on the international stage. The US has emitted more carbon pollution into the atmosphere than any other country, it currently leads the world in per capita emissions, and its the worlds richest economy. If anybody should be a leader at the table in talks about climate finance, its the US. And yet, Trump is coming into power soon, and weve all seen this film before. Last time Trump was in office, he pulled the US out of the Paris Agreement. Hes made promises to do it againand could go one step further by backing out of the UN Framework Convention on Climate Change (UNFCCC) altogether. If leaving the Paris Agreement is walking away from the table, withdrawing from the UNFCCC is like hopping on a rocket and blasting in a different direction. Its a more drastic action and could be tougher to reverse in the future, though experts also arent sure if Trump could technically do this on his own. The uncertainty of what happens next in the US is a cloud hanging over these negotiations. This is going to be harder because we don't have a dynamic and pushy and confident US helping us on climate action, said Camilla Born, an independent climate advisor and former UK senior official at COP26, during an online event last week hosted by Carbon Brief. Some experts are confident that others will step up to fill the gap. There are many drivers of climate action beyond the White House, said Mohamed Adow, founding director of Power Shift Africa, at the CarbonBrief event. If I could characterize the current vibe in the climate world, its uncertainty. But the negotiations over the next couple of weeks could provide clues to what we can expect for the next few years. Just how much will a Trump presidency slow global climate action? Will the European Union step up? Could this cement the rise of China as a climate leader? Well be watching it all. Now read the rest of The Spark Related reading In case you want some additional context from the last few years of these meetings, heres my coverage of last years fight at COP28 over a transition away from fossil fuels, and a newsletter about negotiations over the loss and damages fund at COP27. For the nitty-gritty details about whats on the table at COP29, check out this very thorough explainer from Carbon Brief. DAN THORNBERG/ADOBE STOCK Another thing Trumps election will have significant ripple effects across the economy and our lives. His victory is a tragic loss for climate progress, as my colleague James Temple wrote in an op-ed last week. Give it a read, if you havent already, to dig into some of the potential impacts we might see over the next four years and beyond. Keeping up with climate The US Environmental Protection Agency finalized a rule to fine oil and gas companies for methane emissions. The fee was part of the Inflation Reduction Act of 2022. (Associated Press) This rule faces a cloudy future under the Trump administration; industry groups are already talking about repealing it. (NPR)Speaking of the EPA, Donald Trump chose Lee Zeldin, a former Republican congressman from New York, to lead the agency. Zeldin isnt particularly known for climate or economic policy. (New York Times) Oil giant BP is scaling back its early-stage hydrogen projects. The company revealed in an earnings report that its canceling 18 such projects and currently plans to greenlight between five and 10. (TechCrunch) Investors betting against renewable energy scored big last week, earning nearly $1.2 billion as stocks in that sector tumbled. (Financial Times) Lithium iron phosphate batteries are taking over the world, or at least electric vehicles. These lithium-ion batteries are cheaper and longer-lasting than their nickel-containing cousins, though they also tend to be heavier. (Canary Media) I wrote about this trend last year in a newsletter about batteries and their ingredients. (MIT Technology Review)The US unveiled plans to triple its nuclear energy capacity by 2050. Thats an additional 200 gigawatts worth of consistently available power. (Bloomberg) Five subsea cables that can help power millions of homes just got the green light in Great Britain. The projects will help connect the island to other power grids, as well as to offshore wind farms in Dutch and Belgian waters. (The Guardian)

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Google DeepMind has a new way to look inside an AIs mind We dont know exactly how AI works, or why it works so well. Thats a problem: It could lead us to deploy an AI system in a highly sensitive field like medicine without understanding that it could have critical flaws embedded in its workings. A team at Google DeepMind that studies something called mechanistic interpretability has been working on new ways to let us peer under the hood. It recently released a tool to help researchers understand what is happening when AI is generating an output. Its all part of a push to get a better understanding of exactly what is happening inside an AI model. If we do, well be able to control its outputs more effectively, leading to better AI systems in the future. Read the full story. Scott J Mulligan Whats on the table at this years UN climate conference Talks kicked off this week at COP29 in Baku, Azerbaijan. Running for a couple of weeks each year, the global summit is the largest annual meeting on climate change. The issue on the table this time around: Countries need to agree to set a new goal on how much money should go to developing countries to help them finance the fight against climate change. Complicating things? A US president-elect whose approach to climate is very different from that of the current administration (understatement of the century). This is a big moment that could set the tone for what the next few years of the international climate world looks like. Heres what you need to know about COP29 and how Donald Trumps election is coloring things. Casey Crownhart This story is from The Spark, our weekly newsletter giving you the inside track on all things energy and climate. Sign up to receive it in your inbox every Wednesday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 The FBI is investigating crypto predictions-betting platform Polymarket Its investigating whether the firm allowed US traders to bet on the election. (Bloomberg $)+ Doing so would have been a violation of an agreement with the US government. (NYT $)+ Polymarket claims to be a fully transparent prediction market. (WSJ $)2 OpenAI is calling for the US government to invest in AI Without financial support, the US could lose crucial ground to China, it warns. (WP $)+ The firm floated the idea of building a colossal data center. (The Information $) 3 AI-generated Elon Musk propaganda is rife on Facebook Pro-Musk inspiration porn is the content of choice for spammers. (404 Media)+ Trump is surrounding himself with terminally online edgelords. (The Atlantic $)4 The online right has a misogynistic new rallying cry Your body, my choice is being spread by young men seeking to provoke. (New Yorker $)+ The upcoming presidency could usher in an age of gendered regression. (The Guardian)5 Chinas human factory workers are under pressure Robots are creeping into every level of the manufacturing process. (FT $)+ Three reasons robots are about to become way more useful. (MIT Technology Review)Efforts to revitalize native facilities arent exactly going to plan. (6 The future of chipmaking in AmericaWired $)+ Whats next in chips. (MIT Technology Review)7 Blindbox live streaming is thrilling shoppers in ChinaYou never know what youre going to get. (NYT $) 8 What the glacial Earth may have looked like Around 700 million years ago, the entire planet was covered in ice. (Ars Technica)+ Life-seeking, ice-melting robots could punch through Europas icy shell. (MIT Technology Review)9 How to protect the worlds largest single coral colony The newly-discovered colony is the size of two basketball courts. (Vox)+ The race is on to save coral reefsby freezing them. (MIT Technology Review)10 These researchers have reinvented the wheel This morphing wheel can roll over obstacles up to 1.3 times the height of its radius. (Reuters) Quote of the day Shawty crunk, so fresh, so clean. Mark Zuckerberg, Meta CEO-turned rapper, debuts a reworked version of 2002 rap hit Get Low in a tribute to his wife, the Wall Street Journal reports. The big story Marseilles battle against the surveillance state June 2022Across the world, video cameras have become an accepted feature of urban life. Many cities in China now have dense networks of them, and London and New Delhi arent far behind. Now France is playing catch-up. Concerns have been raised throughout the country. But the surveillance rollout has met special resistance in Marseille, Frances second-biggest city.Its unsurprising, perhaps, that activists are fighting back against the cameras, highlighting the surveillance systems overreach and underperformance. But are they succeeding? Read the full story.Fleur Macdonald We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + This years gurning championship winning mugshots do not disappoint.+ What does it mean to have personal style, exactly?+ Amsterdams unofficial police cat is absolutely adorable (and he lives on a boat!)+ Save the wormsthis writer certainly is.

Teaching robots to navigate new environments is tough. You can train them on physical, real-world data taken from recordings made by humans, but thats scarce and expensive to collect. Digital simulations are a rapid, scalable way to teach them to do new things, but the robots often fail when theyre pulled out of virtual worlds and asked to do the same tasks in the real one. Now theres a potentially better option: a new system that uses generative AI models Researchers used the system, called LucidSim, to train a robot dog in parkour, getting it to scramble over a box and climb stairs even though it had never seen any real-world data. The approach demonstrates how helpful generative AI could be when it comes to teaching robots to do challenging tasks. It also raises the possibility that we could ultimately train them in entirely virtual worlds. The research was presented at the Conference on Robot Learning (CoRL) last week. Were in the middle of an industrial revolution for robotics, says Ge Yang, a postdoc at MITs Computer Science and Artificial Intelligence Laboratory, who worked on the project. This is our attempt at understanding the impact of these [generative AI] models outside of their original intended purposes, with the hope that it will lead us to the next generation of tools and models. LucidSim uses a combination of generative AI models to create the visual training data. First the researchers generated thousands of prompts for ChatGPT, getting it to create descriptions of a range of environments that represent the conditions the robot would encounter in the real world, including different types of weather, times of day, and lighting conditions. These included an ancient alley lined with tea houses and small, quaint shops, each displaying traditional ornaments and calligraphy and the sun illuminates a somewhat unkempt lawn dotted with dry patches. These descriptions were fed into a system that maps 3D geometry and physics data onto AI-generated images, creating short videos mapping a trajectory for the robot to follow. The robot draws on this information to work out the height, width, and depth of the things it has to navigatea box or a set of stairs, for example. The researchers tested LucidSim by instructing a four-legged robot equipped with a webcam to complete several tasks, including locating a traffic cone or soccer ball, climbing over a box, and walking up and down stairs. The robot performed consistently better than when it ran a system trained on traditional simulations. In 20 trials to locate the cone, LucidSim had a 100% success rate, versus 70% for systems trained on standard simulations. Similarly, LucidSim reached the soccer ball in another 20 trials 85% of the time, and just 35% for the other system. Finally, when the robot was running LucidSim, it successfully completed all 10 stair-climbing trials, compared with just 50% for the other system. From left: Phillip Isola, Ge Yang, and Alan YuCOURTESY OF MIT CSAIL These results are likely to improve even further in the future if LucidSim draws directly from sophisticated generative video models rather than a rigged-together combination of language, image, and physics models, says Phillip Isola, an associate professor at MIT who worked on the research. The researchers approach to using generative AI is a novel one that will pave the way for more interesting new research, says Mahi Shafiullah, a PhD student at New York University who is using AI models to train robots. He did not work on the project. The more interesting direction I see personally is a mix of both real and realistic imagined data that can help our current data-hungry methods scale quicker and better, he says. The ability to train a robot from scratch purely on AI-generated situations and scenarios is a significant achievement and could extend beyond machines to more generalized AI agents, says Zafeirios Fountas, a senior research scientist at Huawei specializing in braininspired AI. The term robots here is used very generally; were talking about some sort of AI that interacts with the real world, he says. I can imagine this being used to control any sort of visual information, from robots and self-driving cars up to controlling your computer screen or smartphone. In terms of next steps, the authors are interested in trying to train a humanoid robot using wholly synthetic datawhich they acknowledge is an ambitious goal, as bipedal robots are typically less stable than their four-legged counterparts. Theyre also turning their attention to another new challenge: using LucidSim to train the kinds of robotic arms that work in factories and kitchens. The tasks they have to perform require a lot more dexterity and physical understanding than running around a landscape. To actually pick up a cup of coffee and pour it is a very hard, open problem, says Isola. If we could take a simulation that's been augmented with generative AI to create a lot of diversity and train a very robust agent that can operate in a caf, I think that would be very cool.

Ben Zhao remembers well the moment he officially jumped into the fight between artists and generative AI: when one artist asked for AI bananas. A computer security researcher at the University of Chicago, Zhao had made a name for himself by building tools to protect images from facial recognition technology. It was this work that caught the attention of Kim Van Deun, a fantasy illustrator who invited him to a Zoom call in November 2022 hosted by the Concept Art Association, an advocacy organization for artists working in commercial media. On the call, artists shared details of how they had been hurt by the generative AI boom, which was then brand new. At that moment, AI was suddenly everywhere. The tech community was buzzing over image-generating AI models, such as Midjourney, Stable Diffusion, and OpenAIs DALL-E 2, which could follow simple word prompts to depict fantasylands or whimsical chairs made of avocados. But these artists saw this technological wonder as a new kind of theft. They felt the models were effectively stealing and replacing their work. Some had found that their art had been scraped off the internet and used to train the models, while others had discovered that their own names had become prompts, causing their work to be drowned out online by AI knockoffs. Zhao remembers being shocked by what he heard. People are literally telling you theyre losing their livelihoods, he told me one afternoon this spring, sitting in his Chicago living room. Thats something that you just cant ignore. So on the Zoom, he made a proposal: What if, hypothetically, it was possible to build a mechanism that would help mask their art to interfere with AI scraping? I would love a tool that if someone wrote my name and made a prompt, like, garbage came out, responded Karla Ortiz, a prominent digital artist. Just, like, bananas or some weird stuff. That was all the convincing Zhao neededthe moment he joined the cause. Fast-forward to today, and millions of artists have deployed two tools born from that Zoom: Glaze and Nightshade, which were developed by Zhao and the University of Chicagos SAND Lab (an acronym for security, algorithms, networking, and data). Arguably the most prominent weapons in an artists arsenal against nonconsensual AI scraping, Glaze and Nightshade work in similar ways: by adding what the researchers call barely perceptible perturbations to an images pixels so that machine-learning models cannot read them properly. Glaze, which has been downloaded more than 6 million times since it launched in March 2023, adds whats effectively a secret cloak to images that prevents AI algorithms from picking up on and copying an artists style. Nightshade, which I wrote about when it was released almost exactly a year ago this fall, cranks up the offensive against AI companies by adding an invisible layer of poison to images, which can break AI models; it has been downloaded more than 1.6 million times. Thanks to the tools, Im able to post my work online, Ortiz says, and thats pretty huge. For artists like her, being seen online is crucial to getting more work. If they are uncomfortable about ending up in a massive for-profit AI model without compensation, the only option is to delete their work from the internet. That would mean career suicide. Its really dire for us, adds Ortiz, who has become one of the most vocal advocates for fellow artists and is part of a class action lawsuit against AI companies, including Stability AI, over copyright infringement. But Zhao hopes that the tools will do more than empower individual artists. Glaze and Nightshade are part of what he sees as a battle to slowly tilt the balance of power from large corporations back to individual creators. It is just incredibly frustrating to see human life be valued so little, he says with a disdain that Ive come to see as pretty typical for him, particularly when hes talking about Big Tech. And to see that repeated over and over, this prioritization of profit over humanity it is just incredibly frustrating and maddening. As the tools are adopted more widely, his lofty goal is being put to the test. Can Glaze and Nightshade make genuine security accessible for creatorsor will they inadvertently lull artists into believing their work is safe, even as the tools themselves become targets for haters and hackers? While experts largely agree that the approach is effective and Nightshade could prove to be powerful poison, other researchers claim theyve already poked holes in the protections offered by Glaze and that trusting these tools is risky. But Neil Turkewitz, a copyright lawyer who used to work at the Poking the bear The SAND Lab is tight knit, encompassing a dozen or so researchers crammed into a corner of the University of Chicagos computer science building. That space has accumulated somewhat typical workplace detritusa Meta Quest headset here, silly photos of dress-up from Halloween parties there. But the walls are also covered in original art pieces, including a framed painting by Ortiz. Years before fighting alongside artists like Ortiz against AI bros (to use Zhaos words), Zhao and the labs co-leader, Heather Zheng, who is also his wife, had built a record of combating harms posed by new tech. When I visited the SAND Lab in Chicago, I saw how tight knit the group was. Alongside the typical workplace stuff were funny Halloween photos like this one. (Front row: Ronik Bhaskar, Josephine Passananti, Anna YJ Ha, Zhuolin Yang, Ben Zhao, Heather Zheng. Back row: Cathy Yuanchen Li, Wenxin Ding, Stanley Wu, and Shawn Shan.)COURTESY OF SAND LAB Though both earned spots on MIT Technology Reviews 35 Innovators Under 35 list for other work nearly two decades ago, when they were at the University of California, Santa Barbara (Zheng in 2005 for cognitive radios and Zhao a year later for peer-to-peer networks), their primary research focus has become security and privacy. The pair left Santa Barbara in 2017, after they were poached by the new co-director of the University of Chicagos Data Science Institute, Michael Franklin. All eight PhD students from their UC Santa Barbara lab decided to follow them to Chicago too. Since then, the group has developed a bracelet of silence that jams the microphones in AI voice assistants like the Amazon Echo. It has also created a tool called Fawkesprivacy armor, as Zhao put it in a 2020 interview with the New York Timesthat people can apply to their photos to protect them from facial recognition software. Theyve also studied how hackers might steal sensitive information through stealth attacks on virtual-reality headsets, and how to distinguish human art from AI-generated images. Ben and Heather and their group are kind of unique because theyre actually trying to build technology that hits right at some key questions about AI and how it is used, Franklin tells me. Theyre doing it not just by asking those questions, but by actually building technology that forces those questions to the forefront. It was Fawkes that intrigued Van Deun, the fantasy illustrator, two years ago; she hoped something similar might work as protection against generative AI, which is why she extended that fateful invite to the Concept Art Associations Zoom call. That call started something of a mad rush in the weeks that followed. Though Zhao and Zheng collaborate on all the labs projects, they each lead individual initiatives; Zhao took on what would become Glaze, with PhD student Shawn Shan (who was on this years Innovators Under 35 list) spearheading the development of the programs algorithm. In parallel to Shans coding, PhD students Jenna Cryan and Emily Wenger sought to learn more about the views and needs of the artists themselves. They created a user survey that the team distributed to artists with the help of Ortiz. In replies from more than 1,200 artistsfar more than the average number of responses to user studies in computer sciencethe team found that the vast majority of creators had read about art being used to train models, and 97% expected AI to decrease some artists job security. A quarter said AI art had already affected their jobs. Almost all artists also said they posted their work online, and more than half said they anticipated reducing or removing that online work, if they hadnt alreadyno matter the professional and financial consequences. The first scrappy version of Glaze was developed in just a month, at which point Ortiz gave the team her entire catalogue of work to test the model on. At the most basic level, Glaze acts as a defensive shield. Its algorithm identifies features from the image that make up an artist's individual style and adds subtle changes to them. When an AI model is trained on images protected with Glaze, the model will not be able to reproduce styles similar to the original image. A painting from Ortiz later became the first image publicly released with Glaze on it: a young woman, surrounded by flying eagles, holding up a wreath. Its title is Musa Victoriosa, victorious muse. Its the one currently hanging on the SAND Labs walls. Despite many artists initial enthusiasm, Zhao says, Glazes launch caused significant backlash. Some artists were skeptical because they were worried this was a scam or yet another data-harvesting campaign. The lab had to take several steps to build trust, such as offering the option to download the Glaze app so that it adds the protective layer offline, which meant no data was being transferred anywhere. (The images are then shielded when artists upload them.) Soon after Glazes launch, Shan also led the development of the second tool, Nightshade. Where Glaze is a defensive mechanism, Nightshade was designed to act as an offensive deterrent to nonconsensual training. It works by changing the pixels of images in ways that are not noticeable to the human eye but manipulate machine-learning models so they interpret the image as something different from what it actually shows. If poisoned samples are scraped into AI training sets, these samples trick the AI models: Dogs become cats, handbags become toasters. The researchers say only a relatively few examples are enough to permanently damage the way a generative AI model produces images. Currently, both tools are available as free apps or can be applied through the projects website. The lab has also recently expanded its reach by offering integration with the new artist-supported social network Cara, which was born out of a backlash to exploitative AI training and forbids AI-produced content. In dozens of conversations with Zhao and the labs researchers, as well as a handful of their artist-collaborators, its become clear that both groups now feel they are aligned in one mission. I never expected to become friends with scientists in Chicago, says Eva Toorenent, a Dutch artist who worked closely with the team on Nightshade. Im just so happy to have met these people during this collective battle. Images online of Toorenent's Belladonna have been treated with the SAND Lab's Nightshade tool.EVA TOORENENT Her painting Belladonna, which is also another name for the nightshade plant, was the first image with Nightshades poison on it. Its so symbolic, she says. People taking our work without our consent, and then taking our work without consent can ruin their models. Its just poetic justice. No perfect solution The reception of the SAND Labs work has been less harmonious across the AI community. After Glaze was made available to the public, Zhao tells me, someone reported it to sites like VirusTotal, which tracks malware, so that it was flagged by antivirus programs. Several people also started claiming on social media that the tool had quickly been broken. Nightshade similarly got a fair share of criticism when it launched; as TechCrunch reported in January, some called it a virus and, as the story explains, another Reddit user who inadvertently went viral on X questioned Nightshades legality, comparing it to hacking a vulnerable computer system to disrupt its operation. We had no idea what we were up against, Zhao tells me. Not knowing who or what the other side could be meant that every single new buzzing of the phone meant that maybe someone did break Glaze. Both tools, though, have gone through rigorous academic peer review and have won recognition from the computer security community. Nightshade was accepted at the IEEE Symposium on Security and Privacy, and Glaze received a distinguished paper award and the 2023 Internet Defense Prize at the Usenix Security Symposium, a top conference in the field. In my experience working with poison, I think [Nightshade is] pretty effective, says Nathalie Baracaldo, who leads the AI security and privacy solutions team at IBM and has studied data poisoning. I have not seen anything yetand the word yet is important herethat breaks that type of defense that Ben is proposing. And the fact that the team has released the source code for Nightshade for others to probe, and it hasnt been broken, also suggests its quite secure, she adds. At the same time, at least one team of researchers does claim to have penetrated the protections of Glaze, or at least an old version of it. As researchers from Google DeepMind and ETH Zurich detailed in a paper published in June, they found various ways Glaze (as well as similar but less popular protection tools, such as Mist and Anti-DreamBooth) could be circumvented using off-the-shelf techniques that anyone could accesssuch as image upscaling, meaning filling in pixels to increase the resolution of an image as its enlarged. The researchers write that their work shows the brittleness of existing protections and warn that artists may believe they are effective. But our experiments show they are not. Florian Tramr, an associate professor at ETH Zurich who was part of the study, acknowledges that it is very hard to come up with a strong technical solution that ends up really making a difference here. Rather than any individual tool, he ultimately advocates for an almost certainly unrealistic ideal: stronger policies and laws to help create an environment in which people commit to buying only human-created art. What happened here is common in security research, notes Baracaldo: A defense is proposed, an adversary breaks it, andideallythe defender learns from the adversary and makes the defense better. Its important to have both ethical attackers and defenders working together to make our AI systems safer, she says, adding that ideally, all defenses should be publicly available for scrutiny, which would both allow for transparency and help avoid creating a false sense of security. (Zhao, though, tells me the researchers have no intention to release Glazes source code.) Still, even as all these researchers claim to support artists and their art, such tests hit a nerve for Zhao. In Discord chats that were later leaked, he claimed that one of the researchers from the ETH ZurichGoogle DeepMind team doesnt give a shit about people. (That researcher did not respond to a request for comment, but in a blog post he said it was important to break defenses in order to know how to fix them. Zhao says his words were taken out of context.) Zhao also emphasizes to me that the papers authors mainly evaluated an earlier version of Glaze; he says its new update is more resistant to tampering. Messing with images that have current Glaze protections would harm the very style that is being copied, he says, making such an attack useless. This back-and-forth reflects a significant tension in the computer security community and, more broadly, the often adversarial relationship between different groups in AI. Is it wrong to give people the feeling of security when the protections youve offered might break? Or is it better to have some level of protectionone that raises the threshold for an attacker to inflict harmthan nothing at all? Yves-Alexandre de Montjoye, an associate professor of applied mathematics and computer science at Imperial College London, says there are plenty of examples where similar technical protections have failed to be bulletproof. For example, in 2023, de Montjoye and his team probed a digital mask for facial recognition algorithms, which was meant to protect the privacy of medical patients facial images; they were able to break the protections by tweaking just one thing in the programs algorithm (which was open source). Using such defenses is still sending a message, he says, and adding some friction to data profiling. Tools such as TrackMeNotwhich protects users from data profilinghave been presented as a way to protest; as a way to say I do not consent. But at the same time, he argues, we need to be very clear with artists that it is removable and might not protect against future algorithms. While Zhao will admit that the researchers pointed out some of Glazes weak spots, he unsurprisingly remains confident that Glaze and Nightshade are worth deploying, given that security tools are never perfect. Indeed, as Baracaldo points out, the Google DeepMind and ETH Zurich researchers showed how a highly motivated and sophisticated adversary will almost certainly always find a way in. Yet it is simplistic to think that if you have a real security problem in the wild and youre trying to design a protection tool, the answer should be it either works perfectly or dont deploy it, Zhao says, citing spam filters and firewalls as examples. Defense is a constant cat-and-mouse game. And he believes most artists are savvy enough to understand the risk. Offering hope The fight between creators and AI companies is fierce. The current paradigm in AI is to build bigger and bigger models, and there is, at least currently, no getting around the fact that they require vast data sets hoovered from the internet to train on. Tech companies argue that anything on the public internet is fair game, and that it is impossible to build advanced AI tools without copyrighted material; many artists argue that tech companies have stolen their intellectual property So far, the creatives arent exactly winning. A number of companies have already replaced designers, copywriters, and illustrators with AI systems. In one high-profile case, Marvel Studios used AI-generated imagery instead of human-created art in the title sequence of its 2023 TV series Secret Invasion. In another, a radio station fired its human presenters and replaced them with AI. The technology has become a major bone of contention between unions and film, TV, and creative studios, most recently leading to a strike by video-game performers. There are numerous ongoing lawsuits by artists, writers, publishers, and record labels against AI companies. It will likely take years until there is a clear-cut legal resolution. But even a court ruling wont necessarily untangle the difficult ethical questions created by generative AI. Thats why Zhao and Zheng see Glaze and Nightshade as necessary interventionstools to defend original work, attack those who would help themselves to it, and, at the very least, buy artists some time. Having a perfect solution is not really the point. The researchers need to offer something now because the AI sector moves at breakneck speed, Zheng says, means that companies are ignoring very real harms to humans. This is probably the first time in our entire technology careers that we actually see this much conflict, she adds. On a much grander scale, she and Zhao tell me they hope that Glaze and Nightshade will eventually have the power to overhaul how AI companies use art and how their products produce it. It is eye-wateringly expensive to train AI models, and its extremely laborious for engineers to find and purge poisoned samples in a data set of billions of images. Theoretically, if there are enough Nightshaded images on the internet and tech companies see their models breaking as a result, it could push developers to the negotiating table to bargain over licensing and fair compensation. Thats, of course, still a big if. MIT Technology Review reached out to several AI companies, such as Midjourney and Stability AI, which did not reply to requests for comment. A spokesperson for OpenAI, meanwhile, did not confirm any details about encountering data poison but said the company takes the safety of its products seriously and is continually improving its safety measures: We are always working on how we can make our systems more robust against this type of abuse. In the meantime, the SAND Lab is moving ahead and looking into funding from foundations and nonprofits to keep the project going. They also say there has also been interest from major companies looking to protect their intellectual property (though they decline to say which), and Zhao and Zheng are exploring how the tools could be applied in other industries, such as gaming, videos, or music. In the meantime, they plan to keep updating Glaze and Nightshade to be as robust as possible, working closely with the students in the Chicago labwhere, on another wall, hangs Toorenents Belladonna. The painting has a heart-shaped note stuck to the bottom right corner: Thank you! You have given hope to us artists. This story has been updated with the latest download figures for Glaze and Nightshade.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. The AI lab waging a guerrilla war over exploitative AI Back in 2022, the tech community was buzzing over image-generating AI models, such as Midjourney, Stable Diffusion, and OpenAIs DALL-E 2, which could follow simple word prompts to depict fantasylands or whimsical chairs made of avocados. But artists saw this technological wonder as a new kind of theft. They felt the models were effectively stealing and replacing their work. Ben Zhao, a computer security researcher at the University of Chicago, was listening. He and his colleagues have built arguably the most prominent weapons in an artists arsenal against nonconsensual AI scraping: two tools called Glaze and Nightshade that add barely perceptible perturbations to an images pixels so that machine-learning models cannot read them properly.But Zhao sees the tools as part of a battle to slowly tilt the balance of power from large corporations back to individual creators. Read the full story. Melissa Heikkil Have we entered the golden age of plant engineering? In the 1960s, biologists selective breeding of plants helped spark a period of transformative agricultural innovation known as the Green Revolution. By the 1990s, the yields of wheat and rice had doubled worldwide, staving off bouts of recurring famine. The Green Revolution was so successful that dire predictions of worse famine to comefueled by alarming population growthno longer seemed likely. But it had its limitsonly so much yield could be coaxed from plants using conventional breeding techniques. Now, more precise gene-editing technologies could shave years off the time it takes for new plant varieties to make it from the lab to federally approved seed products. Read the full story. Bill Gourgey This piece is from the latest print issue of MIT Technology Review, which is all about the weird and wonderful world of food. If you dont already, subscribe to receive future copies once they land. MIT Technology Review Narrated: Is robotics about to have its own ChatGPT moment? Robots that can do many of the things humans do in the home have been a dream of robotics research since the inception of the field in the 1950s. While engineers have made great progress in getting robots to work in tightly controlled environments like labs and factories, the home has proved difficult to design for. But now, the field is at an inflection point. A new generation of researchers believes that generative AI could give robots the ability to learn new skills and adapt to new environments faster than ever before. This new approach, just maybe, can finally bring robots out of the factory and into the mainstream. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which were publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as its released. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Donald Trump wants Elon Musk to maximize government efficiency Despite claiming to be a department, technically its more of an advisory board. (Wired $)+ It will allegedly operate outside of the federal government. (WSJ $)+ Expect Musk to treat the US government like his loss-making social network. (Bloomberg $)2 The crypto industry has already started lobbying Trump Executives are wasting no time in presenting the President-elect with their wish lists. (NYT $)+ Were witnessing the industrys nascent attempts to make itself institutional. (NY Mag $)+ The Trump Pump is showing no signs of slowing. (CNN)3 Advertisers are considering staging a return to X In a bid to curry favor with Musk and his political leverage. (FT $)+ Silicon Valley is decidedly more Trump-friendly than it used to be. (Insider $)+ Bluesky is starting to look more and more appealing. (Slate $)4 Major AI players are struggling to make new breakthroughs Funneling money into new products isnt having the desired result. (Bloomberg $)5 The worlds e-waste is actually pretty valuable Theres a lot of gold to be stripped out from those old circuit boards. (Economist $)+AI will add to the e-waste problem. Heres what we can do about it. (MIT Technology Review) 6 DNA testing is ushering in a new age of discriminationAnd you could be denied medical or life insurance because of it. (The Atlantic $) + How to delete your 23andMe data. (MIT Technology Review)7 How to build the perfect humanoid robotUnfortunately, theyll be found in factories and warehouses before they make it to our homes. (IEEE Spectrum) + A skeptics guide to humanoid-robot videos. (MIT Technology Review)8 The US is using AI to seek out critical mineralsAccess to regular supplies could lessen its reliance on China and Russia. (Undark Magazine) + The race to produce rare earth elements. (MIT Technology Review)9 Apples AirTags can now share their location with airlines Which should (hopefully) minimize the chances of losing your luggage. (WP $)+ Its next device? An AI wall-mounted tablet, supposedly. (Bloomberg $)10 This new mathematics benchmark is being kept secret To prevent AI models from training against it. (Ars Technica)+ This AI system makes human tutors better at teaching children math. (MIT Technology Review)Quote of the day Dont bring a watermark to a gunfight. AI researcher Oren Etzioni warns the industry to avoid putting too much faith in voluntary standards to actively prevent malicious actors from gaming the system, TechCrunch reports. The big story The great AI consciousness conundrum October 2023 AI consciousness isnt just a devilishly tricky intellectual puzzle; its a morally weighty problem with potentially dire consequences that philosophers, cognitive scientists, and engineers alike are currently grappling with. Fail to identify a conscious AI, and you might unintentionally subjugate a being whose interests ought to matter. Mistake an unconscious AI for a conscious one, and you risk compromising human safety and happiness for the sake of an unthinking, unfeeling hunk of silicon and code. Over the past few decades, a small research community has doggedly attacked the question of what consciousness is and how it works. The effort has yielded real progress. And now, with the rapid advance of AI technology, these insights could offer our only guide to the untested, morally fraught waters of artificial consciousness. Read the full story. Grace Huckins We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Small changes can improve your life, from debobbling your clothes to oiling your keyholes.+ Woah: these fascinating deep sea creatures can turn back the clock on aging and revert to a more youthful form.+ TikTok is really into onions. Yes, onions. + As if filmmaking wasnt stressful enough, these movies were all completed in a single take.

The complexity of biology has long been a double-edged sword for scientific and medical progress. On one hand, the intricacy of systems (like the human immune response) offers countless opportunities for breakthroughs in medicine and healthcare. On the other hand, that very complexity has often stymied researchers, leaving some of the most significant medical challengeslike cancer or autoimmune diseaseswithout clear solutions. The field needs a way to decipher this incredible complexity. Could the rise of agentic AI, artificial intelligence capable of autonomous decision-making and action, be the key to breaking through this impasse? Agentic AI is not just another tool in the scientific toolkit but a paradigm shift: by allowing autonomous systems to not only collect and process data but also to independently hypothesize, experiment, and even make decisions, agentic AI could fundamentally change how we approach biology. The mindboggling complexity of biological systems To understand why agentic AI holds so much promise, we first need to grapple with the scale of the challenge. Biological systems, particularly human ones, are incredibly complexlayered, dynamic, and interdependent. Take the immune system, for example. It simultaneously operates across multiple levels, from individual molecules to entire organs, adapting and responding to internal and external stimuli in real-time. Traditional research approaches, while powerful, struggle to account for this vast complexity. The problem lies in the sheer volume and interconnectedness of biological data. The immune system alone involves interactions between millions of cells, proteins, and signaling pathways, each influencing the other in real time. Making sense of this tangled web is almost insurmountable for human researchers. Enter AI agents: How can they help? This is where agentic AI steps in. Unlike traditional machine learning models, which require vast amounts of curated data and are typically designed to perform specific, narrow tasks, agentic AI systems can ingest unstructured and diverse datasets from multiple sources and can operate autonomously with a more generalist approach. Beyond this, AI agents are unbound by conventional scientific thinking. They can connect disparate domains and test seemingly improbable hypotheses that may reveal novel insights. What might initially appear as a counterintuitive series of experiments could help uncover hidden patterns or mechanisms, generating new knowledge that can form the foundation for breakthroughs in areas like drug discovery, immunology, or precision medicine. These experiments are executed at unprecedented speed and scale through robotic, fully automated laboratories, where AI agents conduct trials in a continuous, round-the-clock workflow. These labs, equipped with advanced automation technologies, can handle everything from ordering reagents, preparing biological samples, to conducting high-throughput screenings. In particular, the use of patient-derived organoids3D miniaturized versions of organs and tissuesenables AI-driven experiments to more closely mimic the real-world conditions of human biology. This integration of agentic AI and robotic labs allows for large-scale exploration of complex biological systems, and has the potential to rapidly accelerate the pace of discovery. From agentic AI to AGI Owkins next frontier: Unlocking the immune system with agentic AI Agentic AI has already begun pushing the boundaries of whats possible in biology, but the next frontier lies in fully decoding one of the most complex and crucial systems in human health: the immune system. Owkin is building the foundations for an advanced form of intelligencean AGIcapable of understanding the immune system in unprecedented detail. The next evolution of our AI ecosystem, called Owkin K, could redefine how we understand, detect, and treat immune-related diseases like cancer and immuno-inflammatory disorders. Owkin K envisions a coordinated community of specialized AI agents that can autonomously access and interpret comprehensive scientific literature, large-scale biomedical data, and tap into the power of Owkins discovery engines. These agents are capable of planning and executing experiments in fully automated, robotized wet labs, where patient-derived organoids simulate real-world human biology. The results of these experiments feed back into the system, enabling continuous learning and refinement of the AI agents models. What makes Owkin K particularly exciting is its potential to tackle the immune systema biological network so complex that human intelligence alone has struggled to unravel it. By deploying AI agents with the ability to explore this intricate web autonomously, the project could reveal new therapeutic targets and strategies for immuno-oncology and autoimmune diseases, potentially accelerating the development of groundbreaking treatments. Navigating challenges and ethical considerations of agentic AI Of course, such powerful technology comes with significant challenges and ethical considerations, including trust, security, and transparency. But we must tackle these challenges as agentic AI becomes more integrated into healthcare and research. For example, we can develop mitigation plans that include rigorous validation protocols, real-time human oversight, and regulatory frameworks designed to ensure safety, accountability, and transparency. By prioritizing ethical design and close collaboration between AI systems and human experts, we can harness the potential of agentic AI while minimizing its risks. The future of biological research with agentic AI Agentic AI has the potential to reshape not just healthcare, but the very foundations of biological research. By allowing autonomous systems to explore the unknown, we may unlock new levels of understanding in areas like immunology, neuroscience, and genomicsfields that are currently constrained by the limits of human comprehension. We could soon see a world where AI-driven labs operate around the clock, pushing the boundaries of biology at speeds and scales that far exceed human capabilities. This would not only accelerate scientific discovery but also create new possibilities for personalized medicine, disease prevention, and even longevity. In the end, agentic AI may be more than just another tool for researchers. It could be the key to understanding life itselfone autonomous decision at a time. Davide Mantiero, PhD, Eric Durand, PhD, and Darius Meadon also contributed to this article. This content was produced by Owkin. It was not written by MIT Technology Reviews editorial staff.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. When we talk about the global race for AI dominance, the conversation often focuses on tensions between the US and China, and European efforts at regulating the technology. But its high time we talked about another player: Africa. AsMIT Technology Reviewhas written before, AI is creating anew colonial world order, where the technology is enriching a small minority of people at the expense of the rest of the world. African AI researchers are determined to change that. Theyre forging their own path, developing tools that answer the needs of Africans, in their own languages. However, they face many barriers. AI research is eye-wateringly expensive, and African startups and researchers get a fraction as much funding as their Western or Asian counterparts. They have to innovate and rely on open-source resources to do more with less. Despite that, the African AI story reflects not only persistence and innovation, but a determination to preserve cultures and shape how AI technologies are used on the continent.Read more herefrom Abdullahi Tsanni, who went to this years Deep Learning Indaba, a machine-learning conference held annually in Senegal, to learn about the opportunities and barriers the African AI scene faces. And then some personal news!This edition will be my last newsletter, and from next week youll be in the extremely capable hands of my colleagueJames ODonnell. Its been a delight writing this newsletter for the past two or so years, and Im so grateful youve joined me on this journey covering everything fromsnowballs of bullshittoTaylor Swifts deepfakes. Im not going anywhere, though. Ill be diving deeper into the AI beat at MIT Technology Review to bring you stories on whats happening in AI and how the technology is changing us and our societies. Stay tuned for more! Finally, while I have you, this week were running our biggest sale of the year, with 50% off an annual subscription to MIT Technology Review. New subscribers receive a free digital report on generative AI and the future of work.Subscribe here. Now read the rest of The Algorithm Deeper Learning Why AI could eat quantum computings lunch Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that theyll be a game changer for fields as diverse as finance, drug discovery, and logistics. Those expectations have been especially high in physics and chemistry, where the weird effects of quantum mechanics come into play. In theory, this is where quantum computers could have a huge advantage over conventional machines. Enter AI:But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computings purported home turf might not be so safe after all. Given the pace of recent advances, a growing number of researchers are now asking whether AI could solve a substantial chunk of the most interesting problems in chemistry and materials science before large-scale quantum computers become a reality.Read more from Edd Gent here. Bits and Bytes The Saudis are planning a $100 billion AI powerhouseSpeaking of the race for AI dominance, this piece looks at how Saudi Arabia wants in on AI action. And its putting its money where its mouth is. The country is investing a massive sum to develop a tech hub that it hopes will rival the neighboring United Arab Emirates. (Bloomberg) AI is making it harder to believe what is real and what is notTwo recent examples show just how influential AI slop can be in warping our sense of reality. In Dublin,crowds gatheredin the city center to wait for a Halloween parade to take place. There was no parade planned, but the listing was created by AI and then picked up by social media users and local media. By way of contrast, some social media users dismissedshocking images of the devastating recent floods in Spainas AI-generated, although they were entirely real. AI companies are getting comfortable offering their technology to the militaryMilitaries around the world have been pouring money into new technologies, including AI. Meta and Anthropic are the latest tech companies to start courting them, joining the likes of Google and OpenAI. (The Washington Post) OpenAI is shifting its strategy as the improvement in its AI tools slows downThe current paradigm in AI development is to make things bigger to make them better. But OpenAIs new model, code-named Orion, only performs slightly better than its predecessors. Instead, OpenAI is shifting to improving models after their initial training. (The Information)

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Generative AI taught a robot dog to scramble around a new environment Teaching robots to navigate new environments is tough. You can train them on physical, real-world data taken from recordings made by humans, but thats scarce, and expensive to collect. Digital simulations are a rapid, scalable way to teach them to do new things, but the robots often fail when theyre pulled out of virtual worlds and asked to do the same tasks in the real one. Now, theres potentially a better option: a new system that uses generative AI models in conjunction with a physics simulator to develop virtual training grounds that more accurately mirror the physical world. Robots trained using this method worked with a higher success rate than those trained using more traditional techniques during real-world tests. Researchers used the system, called LucidSim, to train a robot dog in parkour, getting it to scramble over a box and climb stairs, despite never seeing any real world data. The approach demonstrates how helpful generative AI could be when it comes to teaching robots to do challenging tasks. It also raises the possibility that we could ultimately train them in entirely virtual worlds. Read the full story. Rhiannon Williams Africas AI researchers are ready for takeoff When we talk about the global race for AI dominance, the conversation often focuses on tensions between the US and China, and European efforts at regulating the technology. But its high time we talk about another player: Africa. African AI researchers are forging their own path, developing tools that answer the needs of Africans, in their own languages. Their story is not only one of persistence and innovation, but of preserving cultures and fighting to shape how AI technologies are used on their own continent. However, they face many barriers. Read the full story.Melissa Heikkil This story is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 How Silicon Valley is planning to work with Donald Trump Avoiding antitrust regulation and boosting growth are at the top of Big Techs agenda. (WP $)+ Tech executives overwhelmingly supported Kamala Harris. (Vox)+ Trumps policies could make it harder to hire and retain overseas talent. (Insider $)+ Immigrant tech workers are rushing to secure visas before Trumps inauguration. (Forbes $)2 People are abandoning X following the US election result Threads and Bluesky are experiencing an influx of new users. (Bloomberg $)+ Trump loved Twitter during his first Presidency. Will he during his second? (Insider $)3 The Biden administration plans to back a controversial cybercrime treatyCritics fear it could be abused by authoritarian regimes to pursue dissidents. (Politico)+ The treaty would also make electronic evidence more available to the US. (Bloomberg $) 4 DNA testing firm 23andMe is firing 40% of its workforce Things arent looking good for the embattled company. (WSJ $)+ The company is axing all its therapy programs, too. (Reuters)+ How to delete your 23andMe data. (MIT Technology Review) 5 How oil and gas companies are masking their methane emissions The odorless, colorless gas is notoriously tough to track, but satellites are changing that. (FT $)+ Even if we reach net zero, parts of the planet will keep getting warmer. (New Scientist $)+ Why methane emissions are still a mystery. (MIT Technology Review)6 This database tracks license plate cameras across the world The project, called DeFlock, aims to give drivers the choice to avoid certain routes. (404 Media)7 Baidu has unveiled its AI-integrated smart glasses The device can track calorie consumption, among other features. (FT $)+ Smartglasses are a growing trend in China. (SCMP $)+ The coolest thing about smart glasses is not the AR. Its the AI. (MIT Technology Review)8 Everything we know about Uranus is wrongA brief flyby 40 years ago coincided with a rare spike in solar activity. (NYT $) 9 How Ukraine is rewilding amid the war Ecologists believe the conflicts catastrophes can birth environmental gains. (Undark Magazine)+ Ukraine has a plan for getting Trump onside. (Vox)10 To find alien life, look to the mountains Who knows whats trapped under tectonic plates? (The Atlantic $)Quote of the day "I did not say I was uncomfortable talking about it. I said we're not going to talk about it. Michael Barratt, an astronaut and medical doctor, refuses to elaborate on a medical issue an astronaut experienced during a recent mission, Ars Technica reports. The big story Zimbabwes climate migration is a sign of whats to come December 2021 Julius Mutero has spent his entire adult life farming a three-hectare plot in Zimbabwe, but has harvested virtually nothing in the past six years. He is just one of the 86 million people in sub-Saharan Africa who the World Bank estimates will migrate domestically by 2050 because of climate change. In Zimbabwe, farmers who have tried to stay put and adapt have found their efforts woefully inadequate in the face of new weather extremes. Droughts have already forced tens of thousands from their homes. But their desperate moves are creating new competition for water in the region, and tensions may soon boil over. Read the full story. Andrew Mambondiyani We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.)+ Heres how to make perfect cacio e pepe every time.+ New York is a wonderful placeeven if youre a native New Yorker, theres always something new to try for the first time.+ The 2024 Natures Best Photo Awards are full of delights.+ Good luck to the brave souls skiing in central London.

Kessel Okinga-Koumu paced around a crowded hallway. It was her first time presenting at the Deep Learning Indaba, she told the crowd gathered to hear her, filled with researchers from Africas machine-learning community. The annual weeklong conference (Indaba is a Zulu word for gathering), was held most recently in September at Amadou Mahtar Mbow University in Dakar, Senegal. It attracted over 700 attendees to hear aboutand debatethe potential of Africa-centric AI and how its being deployed in agriculture, education, health care, and other critical sectors of the continents economy. A 28-year-old computer science student at the University of the Western Cape in Cape Town, South Africa, Okinga-Koumu spoke about how shes tackling a common problem: the lack of lab equipment at her university. Lecturers have long been forced to use chalkboards or printed 2D representations of equipment to simulate practical lessons that need microscopes, centrifuges, or other expensive tools. In some cases, they even ask students to draw the equipment during practical lessons, she lamented. Okinga-Koumu pulled a phone from the pocket of her blue jeans and opened a prototype web app shes built. Using VR and AI features, the app allows students to simulate using the necessary lab equipmentexploring 3D models of the tools in a real-world setting, like a classroom or lab. Students could have detailed VR of lab equipment, making their hands-on experience more effective, she said. Established in 2017, the Deep Learning Indaba now has chapters in 47 of the 55 African nations and aims to boost AI development across the continent by providing training and resources to African AI researchers like Okinga-Koumu. Africa is still early in the process of adopting AI technologies, but organizers say the continent is uniquely hospitable to it for several reasons, including a relatively young and increasingly well-educated population, a rapidly growing ecosystem of AI startups, and lots of potential consumers. The building and ownership of AI solutions tailored to local contexts is crucial for equitable development, says Shakir Mohamed, a senior research scientist at Google DeepMind and cofounder of the organization sponsoring the conference. Africa, more than other continents in the world, can address specific challenges with AI and will benefit immensely from its young talent, he says: There is amazing expertise everywhere across the continent. However, researchers ambitious efforts to develop AI tools that answer the needs of Africans face numerous hurdles. The biggest are inadequate funding and poor infrastructure. Not only is it very expensive to build AI systems, but research to provide AI training data in original African languages has been hamstrung by poor financing of linguistics departments at many African universities and the fact that citizens increasingly don't speak or write local languages themselves. Limited internet access and a scarcity of domestic data centers also mean that developers might not be able to deploy cutting-edge AI capabilities. DEEP LEARNING INDABA 2024 Complicating this further is a lack of overarching policies or strategies for harnessing AIs immense benefitsand regulating its downsides. While there are various draft policy documents, researchers are in conflict over a continent-wide strategy. And they disagree about which policies would most benefit Africa, not the wealthy Western governments and corporations that have often funded technological innovation. Taken together, researchers worry, these issues will hold Africas AI sector back and hamper its efforts to pave its own pathway in the global AI race. On the cusp of change Africas researchers are already making the most of generative AIs impressive capabilities. In South Africa, for instance, to help address the HIV epidemic, scientists have designed an app called Your Choice, powered by an LLM-based chatbot that interacts with people to obtain their sexual history without stigma or discrimination. In Kenya, farmers are using AI apps to diagnose diseases in crops and increase productivity. And in Nigeria, Awarri, a newly minted AI startup, is trying to build the countrys first large language model, with the endorsement of the government, so that Nigerian languages can be integrated into AI tools. The Deep Learning Indaba is another sign of how Africas AI research scene is starting to flourish. At the Dakar meeting, researchers presented 150 posters and 62 papers. Of those, 30 will be published in top-tier journals, according to Mohamed. Meanwhile, an analysis of 1,646 publications in AI between 2013 and 2022 found a significant increase in publications from Africa. And Masakhane, a cousin organization to Deep Learning Indaba that pushes for natural-language-processing research in African languages, has released over 400 open-source models and 20 African-language data sets since it was founded in 2018. These metrics speak a lot to the capacity building that's happening, says Kathleen Siminyu, a computer scientist from Kenya, who researches NLP tools for her native Kiswahili. Were starting to see a critical mass of people having basic foundational skills. They then go on to specialize. She adds: Its like a wave that cannot be stopped. Khadija Ba, a Senegalese entrepreneur and investor at the pan-African VC fund P1 Ventures who was at this years conference, says that she sees African AI startups as particularly attractive because their local approaches have potential to be scaled for the global market. African startups often build solutions in the absence of robust infrastructure, yet these innovations work efficiently, making them adaptable to other regions facing similar challenges, she says. In recent years, funding in Africas tech ecosystem has picked up: VC investment totaled $4.5 billion last year, more than double what it was just five years ago, according to a report by the African Private Capital Association. And this October, Google announced a $5.8 million commitment to support AI training initiatives in Kenya, Nigeria, and South Africa. But researchers say local funding remains sluggish. Take the Google-backed fund rolled out, also in October, in Nigeria, Africas most populous country. It will pay out $6,000 each to 10 AI startupsnot even enough to purchase the equipment needed to power their systems. Lilian Wanzare, a lecturer and NLP researcher at Maseno University in Kisumu, Kenya, bridles at African governments lackadaisical support for local AI initiatives and complains as well that the government charges exorbitant fees for access to publicly generated data, hindering data sharing and collaboration. [We] researchers are just blocked, she says. The government is saying theyre willing to support us, but the structures have not been put in place for us. Language barriers Researchers who want to make Africa-centric AI dont face just insufficient local investment and inaccessible data. There are major linguistic challenges, too. During one discussion at the Indaba, Ife Adebara, a Nigerian computational linguist, posed a question: How many people can write a bachelors thesis in their native African language? Zero hands went up. Then the audience disintegrated into laughter. Africans want AI to speak their local languages, but many Africans cannot speak and write in these languages themselves, Adebara said. Although Africa accounts for one-third of all languages in the world, many oral languages are slowly disappearing, their population of native speakers declining. And LLMs developed by Western-based tech companies fail to serve African languages; they dont understand locally relevant context and culture. For Adebara and others researching NLP tools, the lack of people who have the ability to read and write in African languages poses a major hurdle to development of bespoke AI-enabled technologies. Without literacy in our local languages, the future of AI in Africa is not as bright as we think, she says. On top of all that, theres little machine-readable data for African languages. One reason is that linguistic departments in public universities are poorly funded, Adebara says, limiting linguists participation in work that could create such data and benefit AI development. This year, she and her colleagues established EqualyzAI, a for-profit company seeking to preserve African languages through digital technology. They have built voice tools and AI models, covering about 517 African languages. Lelapa AI, a software company thats building data sets and NLP tools for African languages, is also trying to address these language-specific challenges. Its cofounders met in 2017 at the first Deep Learning Indaba and launched the company in 2022. In 2023, it released its first AI tool, Vulavula, a speech-to-text program that recognizes several languages spoken in South Africa. This year, Lelapa AI released InkubaLM, a first-of-its-kind small language model that currently supports a range of African languages: IsiXhosa, Yoruba, Swahili, IsiZulu, and Hausa. InkubaLM can answer questions and perform tasks like English translation and sentiment analysis. In tests, it performed as well as some larger models. But its still in early stages. The hope is that InkubaLM will someday power Vulavula, says Jade Abbott, cofounder and chief operating officer of Lelapa AI. Its the first iteration of us really expressing our long-term vision of what we want, and where we see African AI in the future, Abbott says. What were really building is a small language model that punches above its weight. InkubaLM is trained on two open-source data sets with 1.9 billion tokens, built and curated by Masakhane and other African developers who worked with real people in local communities. They paid native speakers of languages to attend writing workshops to create data for their model. Fundamentally, this approach will always be better, says Wanzare, because its informed by people who represent the language and culture. A clash over strategy Another issue that came up again and again at the Indaba was that Africas AI scene lacks the sort of regulation and support from governments that you find elsewhere in the worldin Europe, the US, China, and, increasingly, the Middle East. Of the 55 African nations, only sevenSenegal, Egypt, Mauritius, Rwanda, Algeria, Nigeria, and Beninhave developed their own formal AI strategies. And many of those are still in the early stages. A major point of tension at the Indaba, though, was the regulatory framework that will govern the approach to AI across the entire continent. In March, the African Union Development Agency published a white paper, developed over a three-year period, that lays out this strategy. The 200-page document includes recommendations for industry codes and practices, standards to assess and benchmark AI systems, and a blueprint of AI regulations for African nations to adopt. The hope is that it will be endorsed by the heads of African governments in February 2025 and eventually passed by the African Union. But in July, the African Union Commission in Addis Ababa, Ethiopia, another African governing body that wields more power than the development agency, released a rival continental AI strategya 66-page document that diverges from the initial white paper. Its unclear whats behind the second strategy, but Seydina Ndiaye, a program director at the Cheikh Hamidou Kane Digital University in Dakar who helped draft the development agencys white paper, claims it was drafted by a tech lobbyist from Switzerland. The commissions strategy calls for African Union member states to declare AI a national priority, promote AI startups, and develop regulatory frameworks to address safety and security challenges. But Ndiaye expressed concerns that the document does not reflect the perspectives, aspirations, knowledge, and work of grassroots African AI communities. Its a copy-paste of whats going on outside the continent, he says. Vukosi Marivate, a computer scientist at the University of Pretoria in South Africa who helped found the Deep Learning Indaba and is known as an advocate for the African machine-learning movement, expressed fury over this turn of events at the conference. These are things we shouldnt accept, he declared. The room full of data wonks, linguists, and international funders brimmed with frustration. But Marivate encouraged the group to forge ahead with building AI that benefits Africans: We dont have to wait for the rules to act right, he said. Barbara Glover, a program manager for the African Union Development Agency, acknowledges that AI researchers are angry and frustrated. Theres been a push to harmonize the two continental AI strategies, but she says the process has been fractious: That engagement didnt go as envisioned. Her agency plans to keep its own version of the continental AI strategy, Glover says, adding that it was developed by African experts rather than outsiders. We are capable, as Africans, of driving our own AI agenda, she says. DEEP LEARNING INDABA 2024 This all speaks to a broader tension over foreign influence in the African AI scene, one that goes beyond any single strategic document. Mirroring the skepticism toward the African Union Commission strategy, critics say the Deep Learning Indaba is tainted by its reliance on funding from big foreign tech companies; roughly 50% of its $500,000 annual budget comes from international donors and the rest from corporations like Google DeepMind, Apple, Open AI, and Meta. They argue that this cash could pollute the Indabas activities and influence the topics and speakers chosen for discussion. But Mohamed, the Indaba cofounder who is a researcher at Google DeepMind, says that almost all that goes back to our beneficiaries across the continent, and the organization helps connect them to training opportunities in tech companies. He says it benefits from some of its cofounders ties with these companies but that they do not set the agenda. Ndiaye says that the funding is necessary to keep the conference going. But we need to have more African governments involved, he says. To Timnit Gebru, founder and executive director at the nonprofit Distributed AI Research Institute (DAIR), which supports equitable AI research in Africa, the angst about foreign funding for AI development comes down to skepticism of exploitative, profit-driven international tech companies. Africans [need] to do something different and not replicate the same issues were fighting against, Gebru says. She warns about the pressure to adopt AI for everything in Africa, adding that theres a lot of push from international development organizations to use AI as an antidote for all Africas challenges. Siminyu, who is also a researcher at DAIR, agrees with that view. She hopes that African governments will fund and work with people in Africa to build AI tools that reach underrepresented communitiestools that can be used in positive ways and in a context that works for Africans. We should be afforded the dignity of having AI tools in a way that others do, she says.

Rather than analyzing the news this week, I thought Id lift the hood a bit on how we make it. Ive spent most of this year being pretty convinced that Donald Trump would be the 47th president of the United States. Even so, like most people, I was completely surprised by the scope of his victory. By taking the lions share not just in the Electoral College but also the popular vote, coupled with the wins in the Senate (and, as I write this, seemingly the House) and ongoing control of the courts, Trump has done far more than simply eke out a win. This level of victory will certainly provide the political capital to usher in a broad sweep of policy changes. Some of these changes will be well outside our lane as a publication. But very many of President-elect Trumps stated policy goals will have direct impacts on science and technology. Some of the proposed changes would have profound effects on the industries and innovations weve covered regularly, and for years. When he talks about his intention toend EV subsidies, hit the brakes on FTC enforcement actions on Big Tech, ease the rules on crypto, or impose a 60 percent tariff on goods from China, these are squarely in our strike zone and we would be remiss not to explore the policies and their impact in detail. And so I thought I would share some of my remarks from our edit meeting on Wednesday morning, when we woke up to find out that the world had indeed changed. I think its helpful for our audience if we are transparent and upfront about how we intend to operate, especially over the next several months that will likely be, well, chaotic. This is a moment when our jobs are more important than ever. There will be so much noise and heat out there in the coming weeks and months, and maybe even years. The next six months in particular will be a confusing time for a lot of people. We should strive to be the signal in that noise. We have extremely important stories to write about the role of science and technology in the new administration. There are obvious stories for us to take on in regards to climate, energy, vaccines, womens health, IVF, food safety, chips, China, and Im sure a lot more, that people are going to have all sorts of questions about. Lets start by making a list of questions we have ourselves. Some of the people and technologies we cover will be ascendant in all sorts of ways. We should interrogate that power. Its important that we take care in those stories not to be speculative or presumptive. To always have the facts buttoned up. To speak the truth and be unassailable in doing so. Do we drop everything and only cover this? No. But it will certainly be a massive story that affects nearly all others. This election will be a transformative moment for society and the world. Trump didnt just win, he won a mandate. And hes going to change the country and the global order as a result. The next few weeks will see so much speculation as to what it all means. So much fear, uncertainty, and doubt. There is an enormous amount of bullshit headed down the line. People will be hungry for sources they can trust. We should be there for that. Lets leverage our credibility, not squander it. We are not the resistance. We just want to tell the truth. So lets take a breath, and then go out there and do our jobs. I like to tell our reporters and editors that our coverage should be free from either hype or cynicism. I think thats especially true now. Im also very interested to hear from our readers: What questions do you have? What are the policy changes or staffing decisions you are curious about? Please drop me a line atmat.honan@technologyreview.comIm eager to hear from you. If someone forwarded you this edition of The Debrief, you cansubscribe here. Now read the rest of The Debrief The News Palmer Luckey, who was ousted from Facebook over his support for the last Trump administration and went into defense contracting, is poised to grow in influence under a second administration. He recently talked to MIT Technology Review about how the Pentagon is using mixed reality. What does Donald Trumps relationship with Elon Musk mean for the global EV industry? The Biden administration was perceived as hostile to crypto. The industry can likely expect friendlier waters under Trump Some counter-programming: Life seeking robots could punch through Europas icy surface And for one more big take thats not related to the election: AI vs quantum. AI could solve some of the most interesting scientific problems before big quantum computers become a reality The Chat Every week Ill talk to one of MIT Technology Reviews reporters or editors to find out more about what theyve been working on. This week, I chatted with Melissa Heikkil about her story on how ChatGPT search paves the way for AI agents. Mat: Melissa, OpenAI rolled out web search for ChatGPT last week. It seems pretty cool. But you got at a really interesting bigger picture point about it paving the way for agents. What does that mean? Melissa: Microsoft tried to chip away at Googles search monopoly with Bing, and that didnt really work. Its unlikely OpenAI will be able to make much difference either. Their best bet is try to get users used to a new way of finding information and browsing the web through virtual assistants that can do complex tasks. Tech companies call these agents. ChatGPTs usefulness is limited by the fact that it cant access the internet and doesnt have the most up to date information. By integrating a really powerful search engine into the chatbot, suddenly you have a tool that can help you plan things and find information in a far more comprehensive and immersive way than traditional search, and this is a key feature of the next generation of AI assistants. Mat: What will agents be able to do? Melissa: AI agents can complete complex tasks autonomously and the vision is that they will work as a human assistant would book your flights, reschedule your meetings, help with research, you name it. But I wouldnt get too excited yet. The cutting-edge of AI tech can retrieve information and generate stuff, but it still lacks the reasoning and long-term planning skills to be really useful. AI tools like ChatGPT and Claude also cant interact with computer interfaces, like clicking at stuff, very well. They also need to become a lot more reliable and stop making stuff up, which is still a massive problem with AI. So were still a long way away from the vision becoming reality! I wrote anexplainer on agentsa little while ago with more details. Mat: Is search as we know it going away? Are we just moving to a world of agents that not only answer questions but also accomplish tasks? Melissa: Its really hard to say. We are so used to using online search, and its surprisingly hard to change peoples behaviors. Unless agents become super reliable and powerful, I dont think search is going to go away. Mat: By the way, I know you are in the UK. Did you hear we had an election over here in the US? Melissa: LOL The Recommendation Im just back from a family vacation in New York City, where I was in town to run the marathon. (I get to point this out for like one or two more weeks before the bragging gets tedious, I think.) While there, we went to see The Outsiders. Chat, it was incredible. (Which maybe should go without saying given that it won the Tony for best musical.) But wow. I loved the book and the movie as a kid. But this hit me on an entirely other level. Im not really a cries-at-movies (or especially at musicals) kind of person but I was wiping my eyes for much of the second act. So were very many people sitting around me. Anyway. If youre in New York, or if it comes to your city, go see it. And until then, the soundtrack is pretty amazing on its own. (Heres a great example.)

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. What Africa needs to do to become a major AI player Africa is still early in the process of adopting AI technologies. But researchers say the continent is uniquely hospitable to it for several reasons, including a relatively young and increasingly well-educated population, a rapidly growing ecosystem of AI startups, and lots of potential consumers. However, ambitious efforts to develop AI tools that answer the needs of Africans face numerous hurdles. The biggest are inadequate funding and poor infrastructure. Limited internet access and a scarcity of domestic data centers also mean that developers might not be able to deploy cutting-edge AI capabilities. Complicating this further is a lack of overarching policies or strategies for harnessing AIs immense benefitsand regulating its downsides. Taken together, researchers worry, these issues will hold Africas AI sector back and hamper its efforts to pave its own pathway in the global AI race. Read the full story. Abdullahi Tsanni Science and technology stories in the age of Trump Mat Honan Ive spent most of this year being pretty convinced that Donald Trump would be the 47th president of the United States. Even so, like most people, I was completely surprised by the scope of his victory. This level of victory will certainly provide the political capital to usher in a broad sweep of policy changes. Some of these changes will be well outside our lane as a publication. But very many of President-elect Trumps stated policy goals will have direct impacts on science and technology. So I thought I would share some of my remarks from our edit meeting on Wednesday morning, when we woke up to find out that the world had indeed changed. Read the full story. This story is from The Debrief, the weekly newsletter from our editor in chief Mat Honan. Sign up to receive it in your inbox every Friday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Canada has recorded its first known bird flu case in a human Officials are investigating how the teenager was exposed to the virus. (NPR)+ Canada insists that the risk to the public remains low. (Reuters)+ Why virologists are getting increasingly nervous about bird flu. (MIT Technology Review)2 How MAGA became a rallying call for young men The Republicans online strategy tapped into the desires of disillusioned Gen Z men. (WP $)+ Elon Musk is assembling a list of favorable would-be Trump advisors. (FT $) 3 Trumps victory is a win for the US defense industry Palmer Luckeys Anduril is anticipating a lucrative next four years. (Insider $)+ Heres what Luckey has to say about the Pentagons future of mixed reality. (MIT Technology Review)+ Traditional weapons are being given AI upgrades. (Wired $)4 This year is highly likely to be the hottest on recordThis weeks Cop29 climate summit will thrash out future policies. (The Guardian) + A little-understood contributor to the weather? Microplastics. (Wired $)+ Trumps win is a tragic loss for climate progress. (MIT Technology Review)5 Ukraine is scrambling to repair its power stations Workers are dismantling plants to repair other stations hit by Russian attacks. (WSJ $)+ Meet the radio-obsessed civilian shaping Ukraines drone defense. (MIT Technology Review)6 We need better ways to evaluate LLMs Tech giants are coming up with better methods of measuring these systems. (FT $)+ The improvements in the tech behind ChatGPT appear to be slowing. (The Information $)+ AI hype is built on high test scores. Those tests are flawed. (MIT Technology Review)7 FTX is suing crypto exchange BinanceIt claims Sam Bankman-Fried fraudulently transferred close to $1.8 billion to Binance in 2021. (Bloomberg $) + Meanwhile, bitcoin is surging to new record heights. (Reuters)8 What we know about tech and lonelinessWhile theres little evidence tech directly makes us lonely, theres a strong correlation between the two. (NYT $) 9 Whats next for space policy in the US If one persons interested in the cosmos, its Elon Musk. (Ars Technica)10 Could you save the Earth from a killer asteroid? Its a game thats part strategy, part luck. (New Scientist $)+ Earth is probably safe from a killer asteroid for 1,000 years. (MIT Technology Review) Quote of the day Conflict of interest seems rather quaint. Gita Johar, a professor at Columbia Business School, tells the Guardian about Donald Trump and Elon Musks openly transactional relationship. The big story Quartz, cobalt, and the waste we leave behind May 2024 It is easy to convince ourselves that we now live in a dematerialized ethereal world, ruled by digital startups, artificial intelligence, and financial services. Yet there is little evidence that we have decoupled our economy from its churning hunger for resources. We are still reliant on the products of geological processes like coal and quartz, a mineral thats a rich source of the silicon used to build computer chips, to power our world. Three recent books aim to reconnect readers with the physical reality that underpins the global economy. Each one fills in dark secrets about the places, processes, and lived realities that make the economy tick, and reveals just how tragic a toll the materials we rely on take for humans and the environment. Read the full story. Matthew Ponsford We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.)+ Oscars buzz has already begun, and this years early contenders are an interesting bunch.+ This sweet art project shows how toys age with love + Who doesnt love pretzels? Heres how to make sure they end up with the perfect fluffy interior and a glossy, chewy crust.+ These images of plankton are really quite something.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Trumps win is a tragic loss for climate progress James Temple Donald Trumps decisive victory is a stunning setback for the fight against climate change. The Republican president-elects return to the White House means the US is going to squander precious momentum, unraveling hard-won policy progress that was just beginning to pay off, all for the second time in less than a decade. It comes at a moment when the world cant afford to waste time, with nations far off track from any emissions trajectories that would keep our ecosystems stable and our communities safe. Trump could push the globe into even more dangerous terrain, by defanging President Joe Bidens signature climate laws, exacerbating the dangers of heat waves, floods, wildfires, droughts, and famine and increase deaths and disease from air pollution. And this time round, I fear it will be far worse. Read the full story. The US is about to make a sharp turn on climate policy The past four years have seen the US take climate action seriously, working with the international community and pumping money into solutions. Now, were facing a period where things are going to be very different. This is what the next four years will mean for the climate fight. Read the full story. Casey Crownhart This story is from The Spark, a newsletter we send out every Wednesday. If you want to stay up-to-date with all the latest goings-on in climate and energy, sign up. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Tech leaders are lining up to congratulate Donald Trump In a bid to placate the famously volatile President-elect. (FT $)+ Many are seeking to rebuild bridges that have fractured since his last tenure. (CNBC)+ Particularly Jeff Bezos, who has had a fractious relationship with Trump. (NY Mag $)+ Expect less regulation, more trade upheaval, and a whole lot more Elon Musk. (WP $)2 Election deniers have gone mysteriously silent Its almost as if their claims of fraud were baseless in the first place. (NYT $)+ It looks like influencer marketing campaigns really did change minds. (Wired $)3 How Elon Musk is likely to slash US government spending He has a long history of strategic cost-cutting in his own businesses. (WSJ $)+ His other ventures are on course for favorable government treatment. (Reuters)+ Its easy to forget that Musk claims to have voted Democrat in 2020 and 2016. (WP $) 4 Google could be spared being broken up Trump has expressed skepticism about the antitrust proposal. (Reuters)+ Its far from the only reverse-ferret were likely to see. (Economist $)5 How progressive groups are planning for a future under Trump Alliances are meeting today to form networks of resources. (Fast Company $)6 Australia wants to ban under-16s from accessing social media But its not clear how it could be enforced. (The Guardian)+ The proposed law could come into power as soon as next year. (BBC)+ Roblox has made sweeping changes to its child safety policies. (Bloomberg $)+ Child online safety laws will actually hurt kids, critics say. (MIT Technology Review)7 It looks like OpenAI just paid $10 million for a urlWhy ChatGPT when you could just chat.com? (The Verge) + How ChatGPT search paves the way for AI agents. (MIT Technology Review)8 Women in the US are exploring swearing off men altogetherSocial media interest in a Korean movement advocating for a man-free life is soaring. (WP $) 9 Gen Z cant get enough of manifesting TikTok is teaching them how to will their way to a better life. (Insider $)10 Tattoo artists are divided over whether they should use AI AI-assisted designs have been accused of lacking soul. (WSJ $) Quote of the day "Don't worry, I won't judge much. Maybe just an eye roll here and there." Lily, a sarcastic AI teenage avatar and star of language learning app Duolingo, greets analysts tuning into the companys earning call, Insider reports. The big story The great commercial takeover of low-Earth orbit April 2024 NASA designed the International Space Station to fly for 20 years. It has lasted six years longer than that, though it is showing its age, and NASA is currently studying how to safely destroy the space laboratory by around 2030.The ISS never really became what some had hoped: a launching point for an expanding human presence in the solar system. But it did enable fundamental research on materials and medicine, and it helped us start to understand how space affects the human body. To build on that work, NASA has partnered with private companies to develop new, commercial space stations for research, manufacturing, and tourism. If they are successful, these companies will bring about a new era of space exploration: private rockets flying to private destinations. Theyre already planning to do it around the moon. One day, Mars could follow. Read the full story. David W. Brown We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Who doesnt love a smeared makeup look?+ Time to snuggle up: its officially Nora Ephron season. + Walking backwardsdont knock it til youve tried it. Its surprisingly good for you.+ Feeling stressed? Heres how to calm your mind in times of trouble.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Why AI could eat quantum computings lunch Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that theyll be a game changer for fields as diverse as finance, drug discovery, and logistics. But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computings purported home turf might not be so safe after all. Read the full story. Edd Gent Whats next for reproductive rights in the US This week, it wasnt just the future president of the US that was on the ballot. Ten states also voted on abortion rights. Two years ago, the US Supreme Court overturned Roe v. Wade, a legal decision that protected the right to abortion. Since then, abortion bans have been enacted in multiple states, and millions of people in the US have lost access to local clinics. Now, some states are voting to extend and protect access to abortion. Missouri, a state that has long restricted access, even voted to overturn its ban. But its not all good news for proponents of reproductive rights. Read the full story. Jessica Hamzelou This story is from The Checkup, our weekly newsletter giving you the inside track on all things biotech. Sign up to receive it in your inbox every Thursday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Black Americans received racist texts threatening them with slavery Some of the messages claim to be from Trump supporters or the Trump administration. (WP $)+ What Trumps last tenure as president can teach us about whats coming. (New Yorker $)+ The January 6 rioters are hoping for early pardons and release. (Wired $)2 China is shoring up its economy to the tune of $1.4 trillion Its bracing itself for increased trade tensions with a Trump-governed US. (FT $)+ The countrys chip industry has a plan too. (Reuters)+ Were witnessing the return of Trumponomics. (Economist $)+ Heres how the tech markets have reacted to his reelection. (Insider $)3 How crypto came out on topTrump is all in, even if he previously dismissed it as a scam. (Bloomberg $) + Enthusiasts are hoping for less regulation and more favorable legislation. (Time $)4 A weight-loss drug contributed to the death of a nurse in the UKSusan McGowan took two doses of Mounjaro in the weeks before her death. (BBC)+ Its the first known death to be officially linked to the drug in the UK. (The Guardian) 5 An academics lawsuit against Meta has been dismissed Ethan Zuckerman wanted protection against the firm for building an unfollowing tool. (NYT $)6 How the Republicans won onlineThe right-wing influencer ecosystem is extremely powerful and effective. (The Atlantic $) + The left doesnt really have an equivalent network. (Vox)+ X users are considering leaving the platform in protest (again.) (Slate $)7 What does the future of America's public health look like?Noted conspiracy theorist and anti-vaxxer RFK Jr could be in charge soon. (NY Mag $) + Letting Kennedy go wild on health is not a great sign. (Forbes $)+ His war on fluoride in drinking water is already underway. (Politico)8 An AI-created portrait of Alan Turing has sold for $1 millionJust why? (The Guardian) + Why artists are becoming less scared of AI. (MIT Technology Review)9 How to harness energy from space A relay system of transmitters could help to ping it back to Earth. (IEEE Spectrum)+ The quest to figure out farming on Mars. (MIT Technology Review)10 AI-generated videos are not interesting Thats according to the arbiters of what is and isnt interesting over at Reddit. (404 Media)+ Whats next for generative video. (MIT Technology Review)Quote of the day "That's petty, right? How much does one piece of fruit per day cost?" A former Intel employee reacts to the news the embattled company is planning to restore its free coffee privileges for its staffbut not free fruit, Insider reports. The big story Recapturing early internet whimsy with HTML December 2023 Websites werent always slick digital experiences. There was a time when surfing the web involved opening tabs that played music against your will and sifting through walls of text on a colored background. In the 2000s, before Squarespace and social media, websites were manifestations of individualitybuilt from scratch using HTML, by users who had some knowledge of code. Scattered across the web are communities of programmers working to revive this seemingly outdated approach. And the movement is anything but a superficial appeal to retro aestheticsits about celebrating the human touch in digital experiences. Read the full story. Tiffany Ng We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Sandwiches through the ages is a pretty great subject for a book.+ Art Garfunkel and Paul Simon are getting the band back together! (kind of)+ Instant mashed potatoes have a bad reputation. But it doesnt have to be this way.+ Heres what an actual robot apocalypse would look like (thanks Will!)

Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that theyll be a game changer for fields as diverse as finance, drug discovery, and logistics. Those expectations have been especially high in physics and chemistry, where the weird effects of quantum mechanics come into play. In theory, this is where quantum computers could have a huge advantage over conventional machines. But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computings purported home turf might not be so safe after all. The scale and complexity of quantum systems that can be simulated using AI is advancing rapidly, says Giuseppe Carleo, a professor of computational physics at the Swiss Federal Institute of Technology (EPFL). Last month, he coauthored a paper published in Science showing that neural-network-based approaches are rapidly becoming the leading technique for modeling materials with strong quantum properties. Meta also recently unveiled an AI model trained on a massive new data set of materials that has jumped to the top of a leaderboard for machine-learning approaches to material discovery. Given the pace of recent advances, a growing number of researchers are now asking whether AI could solve a substantial chunk of the most interesting problems in chemistry and materials science before large-scale quantum computers become a reality. The existence of these new contenders in machine learning is a serious hit to the potential applications of quantum computers, says Carleo In my opinion, these companies will find out sooner or later that their investments are not justified. Exponential problems The promise of quantum computers lies in their potential to carry out certain calculations much faster than conventional computers. Realizing this promise will require much larger quantum processors than we have today. The biggest devices have just crossed the thousand-qubit mark, but achieving an undeniable advantage over classical computers will likely require tens of thousands, if not millions. Once that hardware is available, though, a handful of quantum algorithms, like the encryption-cracking Shors algorithm, have the potential to solve problems exponentially faster than classical algorithms can. But for many quantum algorithms with more obvious commercial applications, like searching databases, solving optimization problems, or powering AI, the speed advantage is more modest. And last year, a paper coauthored by Microsofts head of quantum computing, Matthias Troyer, showed that these theoretical advantages disappear if you account for the fact that quantum hardware operates orders of magnitude slower than modern computer chips. The difficulty of getting large amounts of classical data in and out of a quantum computer is also a major barrier. So Troyer and his colleagues concluded that quantum computers should instead focus on problems in chemistry and materials science that require simulation of systems where quantum effects dominate. A computer that operates along the same quantum principles as these systems should, in theory, have a natural advantage here. In fact, this has been a driving idea behind quantum computing ever since the renowned physicist Richard Feynman first proposed the idea. The rules of quantum mechanics govern many things with huge practical and commercial value, like proteins, drugs, and materials. Their properties are determined by the interactions of their constituent particles, in particular their electronsand simulating these interactions in a computer should make it possible to predict what kinds of characteristics a molecule will exhibit. This could prove invaluable for discovering things like new medicines or more efficient battery chemistries, for example. But the intuition-defying rules of quantum mechanicsin particular, the phenomenon of entanglement, which allows the quantum states of distant particles to become intrinsically linkedcan make these interactions incredibly complex. Precisely tracking them requires complicated math that gets exponentially tougher the more particles are involved. That can make simulating large quantum systems intractable on classical machines. This is where quantum computers could shine. Because they also operate on quantum principles, they are able to represent quantum states much more efficiently than is possible on classical machines. They could also take advantage of quantum effects to speed up their calculations. But not all quantum systems are the same. Their complexity is determined by the extent to which their particles interact, or correlate, with each other. In systems where these interactions are strong, tracking all these relationships can quickly explode the number of calculations required to model the system. But in most that are of practical interest to chemists and materials scientists, correlation is weak, says Carleo. That means their particles dont affect each others behavior significantly, which makes the systems far simpler to model. The upshot, says Carleo, is that quantum computers are unlikely to provide any advantage for most problems in chemistry and materials science. Classical tools that can accurately model weakly correlated systems already exist, the most prominent being density functional theory (DFT). The insight behind DFT is that all you need to understand a systems key properties is its electron density, a measure of how its electrons are distributed in space. This makes for much simpler computation but can still provide accurate results for weakly correlated systems. Simulating large systems using these approaches requires considerable computing power. But in recent years theres been an explosion of research using DFT to generate data on chemicals, biomolecules, and materialsdata that can be used to train neural networks. These AI models learn patterns in the data that allow them to predict what properties a particular chemical structure is likely to have, but they are orders of magnitude cheaper to run than conventional DFT calculations. This has dramatically expanded the size of systems that can be modeledto as many as 100,000 atoms at a timeand how long simulations can run, says Alexandre Tkatchenko, a physics professor at the University of Luxembourg. Its wonderful. You can really do most of chemistry, he says. Olexandr Isayev, a chemistry professor at Carnegie Mellon University, says these techniques are already being widely applied by companies in chemistry and life sciences. And for researchers, previously out of reach problems such as optimizing chemical reactions, developing new battery materials, and understanding protein binding are finally becoming tractable. As with most AI applications, the biggest bottleneck is data, says Isayev. Metas recently released materials data set was made up of DFT calculations on 118 million molecules. A model trained on this data achieved state-of-the-art performance, but creating the training material took vast computing resources, well beyond whats accessible to most research teams. That means fulfilling the full promise of this approach will require massive investment. Modeling a weakly correlated system using DFT is not an exponentially scaling problem, though. This suggests that with more data and computing resources, AI-based classical approaches could simulate even the largest of these systems, says Tkatchenko. Given that quantum computers powerful enough to compete are likely still decades away, he adds, AIs current trajectory suggests it could reach important milestones, such as precisely simulating how drugs bind to a protein, much sooner. Strong correlations When it comes to simulating strongly correlated quantum systemsones whose particles interact a lotmethods like DFT quickly run out of steam. While more exotic, these systems include materials with potentially transformative capabilities, like high-temperature superconductivity or ultra-precise sensing. But even here, AI is making significant strides. In 2017, EPFLs Carleo and Microsofts Troyer published a seminal paper in Science In this case, the rules of the game are provided by Schrdingers equation, which can precisely describe a systems quantum state, or wave function. The model plays against itself by arranging particles in a certain configuration and then measuring the systems energy level. The goal is to reach the lowest energy configuration (known as the ground state), which determines the systems properties. The model repeats this process until energy levels stop falling, indicating that the ground stateor something close to ithas been reached. The power of these models is their ability to compress information, says Carleo. The wave function is a very complicated mathematical object, he says. What has been shown by several papers now is that [the neural network] is able to capture the complexity of this object in a way that can be handled by a classical machine. Since the 2017 paper, the approach has been extended to a wide range of strongly correlated systems, says Carleo, and results have been impressive. The Science paper he published with colleagues last month put leading classical simulation techniques to the test on a variety of tricky quantum simulation problems, with the goal of creating a benchmark to judge advances in both classical and quantum approaches. Carleo says that neural-network-based techniques are now the best approach for simulating many of the most complex quantum systems they tested. Machine learning is really taking the lead in many of these problems, he says. These techniques are catching the eye of some big players in the tech industry. In August, researchers at DeepMind showed in a paper in Science that they could accurately model excited states in quantum systems, which could one day help predict the behavior of things like solar cells, sensors, and lasers. Scientists at Microsoft Research have also developed an open-source software suite to help more researchers use neural networks for simulation. One of the main advantages of the approach is that it piggybacks on massive investments in AI software and hardware, says Filippo Vicentini, a professor of AI and condensed-matter physics at cole Polytechnique in France, who was also a coauthor on the Science benchmarking paper: Being able to leverage these kinds of technological advancements gives us a huge edge. There is a caveat: Because the ground states are effectively found through trial and error rather than explicit calculations, they are only approximations. But this is also why the approach could make progress on what has looked like an intractable problem, says Juan Carrasquilla, a researcher at ETH Zurich, and another coauthor on the Science benchmarking paper. If you want to precisely track all the interactions in a strongly correlated system, the number of calculations you need to do rises exponentially with the systems size. But if youre happy with an answer that is just good enough, theres plenty of scope for taking shortcuts. Perhaps theres no hope to capture it exactly, says Carrasquilla. But theres hope to capture enough information that we capture all the aspects that physicists care about. And if we do that, its basically indistinguishable from a true solution. And while strongly correlated systems are generally too hard to simulate classically, there are notable instances where this isnt the case. That includes some systems that are relevant for modeling high-temperature superconductors, according to a 2023 paper in Nature Communications. Because of the exponential complexity, you can always find problems for which you cant find a shortcut, says Frank Noe, research manager at Microsoft Research, who has led much of the companys work in this area. But I think the number of systems for which you cant find a good shortcut will just become much smaller. No magic bullets However, Stefanie Czischek, an assistant professor of physics at the University of Ottawa, says it can be hard to predict what problems neural networks can feasibly solve. For some complex systems they do incredibly well, but then on other seemingly simple ones, computational costs balloon unexpectedly. We dont really know their limitations, she says. No one really knows yet what are the conditions that make it hard to represent systems using these neural networks. Meanwhile, there have also been significant advances in other classical quantum simulation techniques, says Antoine Georges, director of the Center for Computational Quantum Physics at the Flatiron Institute in New York, who also contributed to the recent Science benchmarking paper. They are all successful in their own right, and they are also very complementary, he says. So I dont think these machine-learning methods are just going to completely put all the other methods out of business. Quantum computers will also have their niche, says Martin Roetteler, senior director of quantum solutions at IonQ, which is developing quantum computers built from trapped ions. While he agrees that classical approaches will likely be sufficient for simulating weakly correlated systems, hes confident that some large, strongly correlated systems will be beyond their reach. The exponential is going to bite you, he says. There are cases with strongly correlated systems that we cannot treat classically. Im strongly convinced that thats the case. In contrast, he says, a future fault-tolerant quantum computer with many more qubits than todays devices will be able to simulate such systems. This could help find new catalysts or improve understanding of metabolic processes in the bodyan area of interest to the pharmaceutical industry. Neural networks are likely to increase the scope of problems that can be solved, says Jay Gambetta, who leads IBMs quantum computing efforts, but hes unconvinced theyll solve the hardest challenges businesses are interested in. Thats why many different companies that essentially have chemistry as their requirement are still investigating quantumbecause they know exactly where these approximation methods break down, he says. Gambetta also rejects the idea that the technologies are rivals. He says the future of computing is likely to involve a hybrid of the two approaches, with quantum and classical subroutines working together to solve problems. I dont think theyre in competition. I think they actually add to each other, he says. But Scott Aaronson, who directs the Quantum Information Center at the University of Texas, says machine-learning approaches are directly competing against quantum computers in areas like quantum chemistry and condensed-matter physics. He predicts that a combination of machine learning and quantum simulations will outperform purely classical approaches in many cases, but that wont become clear until larger, more reliable quantum computers are available. From the very beginning, Ive treated quantum computing as first and foremost a scientific quest, with any industrial applications as icing on the cake, he says. So if quantum simulation turns out to beat classical machine learning only rarely, I wont be quite as crestfallen as some of my colleagues. One area where quantum computers look likely to have a clear advantage is in simulating how complex quantum systems evolve over time, says EPFLs Carleo. This could provide invaluable insights for scientists in fields like statistical mechanics and high-energy physics, but it seems unlikely to lead to practical uses in the near term. These are more niche applications that, in my opinion, do not justify the massive investments and the massive hype, Carleo adds. Nonetheless, the experts MIT Technology Review spoke to said a lack of commercial applications is not a reason to stop pursuing quantum computing, which could lead to fundamental scientific breakthroughs in the long run. Science is like a set of nested boxesyou solve one problem and you find five other problems, says Vicentini. The complexity of the things we study will increase over time, so we will always need more powerful tools.

This article first appeared in The Checkup,MIT Technology Reviewsweekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,sign up here. Earlier this week, Americans cast their votes in a seminal presidential election. But it wasnt just the future president of the US that was on the ballot. Ten states also voted on abortion rights. Two years ago, the US Supreme Court overturned Roe v. Wade, a legal decision that protected the right to abortion. Since then, abortion bans have been enacted in multiple states, and millions of people in the US have lost access to local clinics. Now, some states are voting to extend and protect access to abortion. This week, seven states voted in support of such measures. And voters in Missouri, a state that has long restricted access, have voted to overturn its ban. Its not all good news for proponents of reproductive rightssome states voted against abortion access. And questions remain over the impact of a second term under former president Donald Trump, who is set to return to the post in January. Roe v. Wade, the legal decision that enshrined a constitutional right to abortion in the US in 1973, guaranteed the right to an abortion up to the point of fetal viability, which is generally considered to be around 24 weeks of pregnancy. It was overturned by the US Supreme Court in the summer of 2022. Within 100 days of the decision, 13 states had enacted total bans on abortion from the moment of conception. Clinics in these states could no longer offer abortions. Other states also restricted abortion access. In that 100-day period, 66 of the 79 clinics across 15 states stopped offering abortion services, and 26 closed completely, according to research by the Guttmacher Institute. The political backlash to the decision was intense. This week, abortion was on the ballot in 10 states: Arizona, Colorado, Florida, Maryland, Missouri, Montana, Nebraska, Nevada, New York, and South Dakota. And seven of them voted in support of abortion access. The impact of these votes will vary by state. Abortion was already legal in Maryland, for example. But the new measures should make it more difficult for lawmakers to restrict reproductive rights in the future. In Arizona, abortions after 15 weeks had been banned since 2022. There, voters approved an amendment to the state constitution that will guarantee access to abortion until fetal viability. Missouri was the first state to enact an abortion ban once Roe v. Wade was overturned. The states current Right to Life of the Unborn Child Act prohibits doctors from performing abortions unless there is a medical emergency. It has no exceptions for rape or incest. This week, the state voted to overturn that ban and protect access to abortion up to fetal viability. Not all states voted in support of reproductive rights. Amendments to expand access failed to garner enough support in Nebraska, South Dakota, and Florida. In Florida, for example, where abortions after six weeks of pregnancy are banned, an amendment to protect access until fetal viability got 57% of the vote, falling just short of the 60% the state required for it to pass. Its hard to predict how reproductive rights will fare over the course of a second Trump term. Trump himself has been inconsistent on the issue. During his first term, he installed members of the Supreme Court who helped overturn Roe v. Wade. During his most recent campaign he said that decisions on reproductive rights should be left to individual states. Trump, himself a Florida resident, has refused to comment on how he voted in the states recent ballot question on abortion rights. When asked, he said that the reporter who posed the question should just stop talking about that, according to the Associated Press. State decisions can affect reproductive rights beyond abortion access. Just look at Alabama. In February, the Alabama Supreme Court ruled that frozen embryos can be considered children under state law. Embryos are routinely cryopreserved in the course of in vitro fertilization treatment, and the ruling was considered likely to significantly restrict access to IVF in the state. (In March, the state passed another law protecting clinics from legal repercussions should they damage or destroy embryos during IVF procedures, but the status of embryos remains unchanged.) The fertility treatment became a hot topic during this year's campaign. In October, Trump bizarrely referred to himself as the father of IVF. That title is usually reserved for Robert Edwards, the British researcher who won the 2010 Nobel prize in physiology or medicine for developing the technology in the 1970s. Whatever is in store for reproductive rights in the US in the coming months and years, all weve seen so far suggests that its likely to be a bumpy ride. Now read the rest of The Checkup Read more from MIT Technology Review's archive My colleague Rhiannon Williams reported on the immediate aftermath of the decision that reversed Roe v. Wade when it was announced a couple of years ago. The Alabama Supreme Court ruling on embryos could also affect the development of technologies designed to serve as artificial wombs, as Antonio Regalado explained at the time. Other technologies are set to change the way we have babies. Some, which could lead to the creation of children with four parents or none at all, stand to transform our understanding of parenthood. Weve also reported on attempts to create embryo-like structures using stem cells. These structures look like embryos but are created without eggs or sperm. Theres a wild race afoot to make these more like the real thing. But both scientific and ethical questions remain over how far we canandshould go. My colleagues have been exploring what the US election outcome might mean for climate policies. Senior climate editor James Temple writes that Trumps victory is a stunning setback for climate change. And senior reporter Casey Crownhart explains how efforts including a trio of laws implemented by the Biden administration, which massively increased climate funding, could be undone. From around the web Donald Trump has said hell let Robert F. Kennedy Jr. go wild on health. Heres where the former environmental lawyer and independent candidatewho has no medical or public health degreesstands on vaccines, fluoride, and the Affordable Care Act. (New York Times) Bird flu has been detected in pigs on a farm in Oregon. Its a worrying development that virologists were dreading. (The Conversation) And, in case you need it, heres some lighter reading: Scientists are sequencing the DNA of tiny marine plankton for the first time. (Come for the story of the scientific expedition; stay for the beautiful images of jellies and sea sapphires.) (The Guardian) Dolphins are known to communicate with whistles and clicks. But scientists were surprised to find a highly vocal solitary dolphin in the Baltic Sea. They think the animal is engaging in dolphin self-talk. (Bioacoustics) How much do you know about baby animals? Test your knowledge in this quiz. (National Geographic)

At long last, NASAs Europa Clipper mission is on its way. After overcoming financial and technological hurdles, the $5 billion mission launched on October 14 from Floridas Kennedy Space Center. It is now en route to its target: Jupiters ice-covered moon Europa, whose frozen shell almost certainly conceals a warm saltwater ocean. When the spacecraft gets there, it will conduct dozens of close flybys in order to determine what that ocean is like and, crucially, where it might be hospitable to life. Europa Clipper is still years away from its destinationit is not slated to reach the Jupiter system until 2030. But that hasnt stopped engineers and scientists from working on what would come next if the results are promising: a mission capable of finding evidence of life itself. This would likely have three parts: a lander, an autonomous ice-thawing robot, and some sort of self-navigating submersible. Indeed, several groups from multiple countries already have working prototypes of ice-diving robots and smart submersibles that they are set to test in Earths own frigid landscapes, from Alaska to Antarctica, in the next few years But Earths oceans are pale simulacra of Europas extreme environment. To plumb the ocean of this Jovian moon, engineers must work out a way to get missions to survive a never-ending rain of radiation that fries electronic circuits. They must also plow through an ice shell thats at least twice as thick as Mount Everest is tall. There are a lot of hard problems that push up right against the limits of whats possible, says Richard Camilli, an expert on autonomous robotic systems at the Woods Hole Oceanographic Institutions Deep Submergence Laboratory. But youve got to start somewhere, and Earths seas will be a vital testing ground. Were doing something nobody has done before, says Sebastian Meckel, a researcher at the Center for Marine Environmental Sciences at the University of Bremen, Germany, who is helping to develop one such futuristic Europan submersible. If the field tests prove successful, the descendants of these aquatic explorers could very well be those that uncover the first evidence of extraterrestrial life. Hellish descent The hunt for signs of extraterrestrial biology has predominantly taken place on Mars, our dusty, diminutive planetary neighbor. Looking for life in an icy ocean world is a whole new kettle of (alien) fish, but exobiologists think its certainly worth the effort. On Mars, scientists hope to find microscopic evidence of past life on, or just under, its dry and frozen surface. But on Europa, which has a wealth of liquid water (kept warm by Jupiter, whose intense gravity generates plenty of internal friction and heat there), it is possible that microbial critters, and perhaps even more advanced small aquatic animals, may be present in the here and now. The bad news is that Europa is one of the most hostile environments in the solar systemat least, for anything above its concealed ocean. When NASAs Clipper mission arrives in 2030, it will be confronted by an endless storm of high-energy particles being whipped about by Jupiters immense and intense magnetic field, largely raining down onto Europa itself. Its enough to kill a regular person within a few seconds, says Camilli. No human will be present on Europa, but that radiation is so extreme that it can frazzle most electronic circuits. This poses a major hazard for Europa Clipper, which is why its doing only quick flybys of the moon as its orbit around Jupiter periodically dips close. Clipper has an impressive collection of remote sensing tools that will allow it to survey the oceans physical and chemical properties, even though it will never touch the moon itself. But almost all scientists expect that uncovering evidence of biological activity will require something to pierce through the ice shell and swim about in the ocean. An illustration of two Europa exploration concepts from NASA. An ice-melting probe called PRIME sits on the surface of the moon, with small wedge-shaped SWIM robots deployed below.NASA/JPL-CALTECH The good news is that any Europan life-hunting mission has a great technological legacy to build upon. Over the years, scientists have developed and deployed robotic subs that have uncovered a cornucopia of strange life and bizarre geology dwelling in the deep. These include remotely operated vehicles (ROVs), which are often tethered to a surface vessel and are piloted by a person atop the waves, and autonomous underwater vehicles (AUVs), which freely traverse the seas by themselves before reporting back to the surface. Hopeful Europa explorers usually cite an AUV as their best optionsomething that a lander can drop off and let loose in those alien waters that will then return and share its data so it can be beamed back to Earth. The whole idea is very exciting and cool, says Bill Chadwick, a research professor at Oregon State Universitys Hatfield Marine Science Center in Newport, Oregon. But on a technical level, he adds, it seems incredibly daunting. Presuming that a life-finding robotic mission is sufficiently radiation-proof and can land and sit safely on Europas surface, it would then encounter the colossal obstacle that is Europas ice shell, estimated to be 10 to 15 miles thick. Something is going to have to drill or melt its way through all that before reaching the ocean, a process that will likely take several years. And theres no guarantee that the ice is going to be static as youre going through, says Camilli. Thanks to gravitational tugs from Jupiter, and the internal heat they generate, Europa is a geologically tumultuous world, with ice constantly fragmenting, convulsing and even erupting on its surface. How do you deal with that? Europas lack of an atmosphere is also an issue. Say your robot does reach the ocean below all that ice. Thats great, but if the thawed tunnel isnt sealed shut behind the robot, then the higher pressure of the oceanic depths will come up against a vacuum high above. If you drill through and you dont have some kind of pressure control, you can get the equivalent of a blowout, like an oil well, says Camilliand your robot could get rudely blasted into space. Even if you manage to pass through that gauntlet, you must then make sure the diver maintains a link with the surface lander, and with Earth. What would be worse than finally finding life somewhere else and not being able to tell anyone about it? says Morgan Cable, a research scientist at NASAs Jet Propulsion Laboratory (JPL). Pioneering probes What these divers will do when they breach Europas ocean almost doesnt matter at this stage. The scientific analysis is currently secondary to the primary problem: Can robots actually get through that ice shell and survive the journey? A simple way to start is with a cryobota melt probe that can gradually thaw its way through the shell, pulled down by gravity. Thats the idea behind NASAs Probe using Radioisotopes for Icy Moons Exploration, or PRIME. As the name suggests, this cryobot would use the heat from the radioactive decay of an element like plutonium-238 to melt ice. If you know the thickness of the ice shell, you know exactly how many tablespoons of radioactive matter to bring aboard. Once it gets through the ice, the cryobot could unfurl a suite of scientific investigation tools, or perhaps deploy an independent submersible that could work in tandem with the cryobotall while making sure none of that radioactive matter contaminates the ocean. NASAs Sensing with Independent Micro-Swimmers project, for example, has sketched out plans to deploy a school of wedge-shaped robotsa fleet of sleuths that would work together to survey the depths before reporting back to base. These concepts remain hypothetical. To get an idea of whats technically possible, several teams are building and field-testing their own prototype ice divers. One of the furthest-along efforts is the Ocean Worlds Reconnaissance and Characterization of Astrobiological Analogs project, or ORCAA, led by JPL. After some preliminary fieldwork, the group is now ready for prime time; next year, a team will set up camp on Alaskas expansive Juneau Icefield and deploy an eight-foot tall, two-inch wide cryobot. Its goal will be to get through 1,000 feet of ice, through a glasslike upper layer, down into ancient ices, and ultimately into a subglacial lake. ORCAA team members stand by a lake on top of a glacier during Alaska fieldwork. NASA/JPL-CALTECH This cryobot wont be powered by radioactive matter. I dont see NASA and the Department of Energy being game for that yet, says Samuel Howell, an ocean worlds scientist at JPL and the ORCAA principal investigator. Instead, it will be electrically heated (with power delivered via a tether to the surface), and that heat will pump warm water out in front of the cryobot, melting the ice and allowing it to migrate downward. The cryobot will be permanently tethered to the surface, using that link to communicate its rudimentary scientific data and return samples of water back to a team of scientists at base camp atop the ice. Those scientists will act as if they are an astrobiology suite of instruments similar to what might eventually be fitted on a cryobot sent to Europa. The 2025 field experiment has all the pieces of a cryobot mission, says Howell. Were just duct-taping them together and trying to see what breaks. Space scientists and marine engineers are also teaming up at Germanys Center for Marine Environmental Sciences (MARUM) to forge their own underwater explorer. Under the auspices of the Technologies forRapidIcePenetration and SubglacialLakeExploration project, or TRIPLE, they are developing an ice-thawing cryobot, an astrobiological laboratory suite, and an AUV designed to be used in Earths seas and Europas ocean. Their cryobot is somewhat like the one ORCAA is using; its an electrically heated thawing machine tethered to the surface. But onboard MARUMs ice shuttle will be a remarkably small AUV, just 20 inches long and four inches wide. The team plans to deploy both on the Antarctic ice shelf, near the Neumayer III station, in the spring of 2026. Germanys Center for Marine Environmental Sciences is developing a small AUV that it plans to deploy in Antarctica in 2026.MARUM CENTER FOR MARINE ENVIRONMENTAL SCIENCES, UNIVERSITY OF BREMEN. From a surface station, the ice shuttle will thaw its way down through the ice shell, aiming to reach the bitingly cold water hundreds of feet below. Once it does so, a hatch will open and the tiny AUV will be dropped off to swim about (on a probably preprogrammed route), wirelessly communicating with the ice shuttle throughout. It will take a sample of the water, return to the ice shuttle, dock with it, and recharge its batteries. For the field test, the ice shuttle, which will have some rudimentary scientific tools, will return the water sample back to the surface for analysis; for the space mission itself, the idea is that an array of instruments onboard the shuttle will examine that water. As with ORCAA, the scientific aspect of this is not paramount. What were focusing on now is form and function, says project member Ralf Bachmayer, a marine robotics researcher at MARUM. Can their prototype Europan explorer get down to the hidden waters, deploy a scout, and return to base intact? Bachmayer cant wait to find out. For engineers, its a dream come true to work on this project, he says. Swarms and serpents A submersible-like AUV isnt the only way scientists are thinking of investigating icy oceanic moons. JPLs Exobiology Extant Life Surveyor, or EELS, involves a working, wriggling, serpentine robot inspired by the desire to crawl through the vents of Saturns own water-laden moon, Enceladus. The robotic snake has already been field-tested; it recently navigated through the icy crevasses and moulins of the Athabasca Glacier in Alberta, Canada. Although an AUV-like cryobot mission is likely to be the first explorer of an icy oceanic moon, a crazy idea like a robotic snake could work, says Cable, the science lead for EELS. She hopes the project is opening the eyes of scientists and engineers alike to new possibilities when it comes to accessing the hard-to-reach, and often most scientifically compelling, places of planetary environments. It might be that well need such creative, and perhaps unexpected, designs to find our way to Europas ocean. Space agencies exploring the solar system have achieved remarkable things, but NASA has never flown an aqueous instrument before, says Howell. But one day, thanks to this work, it mightand, just maybe, one of them will find life blooming in Europas watery shadows. Robin George Andrews is an award-winning science journalist and doctor of volcanoes based in London. He regularly writes about the Earth, space, and planetary sciences, and is the author of two critically acclaimed books: Super Volcanoes (2021) and How To Kill An Asteroid (October 2024).

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Life-seeking, ice-melting robots could punch through Europas icy shell At long last, NASAs Europa Clipper mission is on its way. It launched on October 14 and is now en route to its target: Jupiters ice-covered moon Europa, whose frozen shell almost certainly conceals a warm saltwater ocean. When the spacecraft gets there, it will conduct dozens of close flybys in order to determine what that ocean is like and, crucially, where it might be hospitable to life. Europa Clipper is still years away from its destinationit is not slated to reach the Jupiter system until 2030. But that hasnt stopped engineers and scientists from working on what would come next if the results are promising: a mission capable of finding evidence of life itself. Read the full story. Robin George Andrews GMOs could reboot chestnut trees Living as long as a thousand years, the American chestnut tree once dominated parts of the Eastern forest canopy, with many Native American nations relying on them for food. But by 1950, the tree had largely succumbed to a fungal blight probably introduced by Japanese chestnuts. As recently as last year, it seemed the 35-year effort to revive the American chestnut might grind to a halt. Now, American Castanea, a new biotech startup, has created more than 2,500 transgenic chestnut seedlings likely the first genetically modified trees to be considered for federal regulatory approval as a tool for ecological restoration. Read the full story.Anya Kamenetz This piece is from the latest print issue of MIT Technology Review, which is all about the weird and wonderful world of food. If you dont already, subscribe to receive future copies once they land. MIT Technology Review Narrated: Why Congos most famous national park is betting big on crypto In an attempt to protect its forests and famous wildlife, Virunga has become the first national park to run a Bitcoin mine. But some are wondering what crypto has to do with conservation. This is our latest story to be turned into a MIT Technology Review Narrated podcast. In partnership with News Over Audio, well be making a selection of our stories available, each one read by a professional voice actor. Youll be able to listen to them on the go or download them to listen to offline.Were publishing a new story each week on Spotify and Apple Podcasts, including some taken from our most recent print magazine. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as its released.The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Donald Trump has won the US Presidential election Hes the first president with a criminal conviction and two impeachments under his belt. (WP $)+ The crypto industry is rejoicing at the news as bitcoin leapt to a record high. (NYT $)+ In fact, a blockchain entrepreneur won the Ohio Senate race. (CNBC)+ What comes next is anyones guess. (The Atlantic $)2 Trumps victory is music to Elon Musks ears Hes been promised a new role as head of a new Department of Government Efficiency. (FT $)+ Musk is being sued over his $1 million giveaways during the election campaign. (Reuters)+ The billionaire used X as his own personal megaphone to stir up dissent. (The Atlantic $) 3 Abortion rights are now under further threat Particularly pills sent by mail. (Vox)+ Trumps approach to discussing abortion has been decidedly mixed. (Bloomberg $)4 Trump could be TikToks last hope for survival in the US Now hes stopped threatening to ban it, that is. (The Information $)5 Perplexity is approaching a $9 billion valuation Thanks to the companys fourth round of funding this year. (WSJ $)+ Microsoft has reportedly expressed interest in acquiring the AI search startup. (The Information $)6 The iPhone could be Apples last major cash cowIts acknowledged that its other devices may never reach the same heady heights. (FT $) + Nvidia has overtaken Apple as the worlds largest company. (Bloomberg $)7 The Mozilla Foundation is getting rid of its advocacy divisionThe team prioritized fighting for a free and open web. (TechCrunch) 8 China plans to slam a spacecraft into an asteroidFollowing in the footsteps of Americas successful 2022 mission. (Economist $) + Watch the moment NASAs DART spacecraft crashed into an asteroid. (MIT Technology Review)9 The Vaticans anime mascot has been co opted into AI porn That didnt take long. (404 Media)10 Gigantic XXL TVs are the gift of the season Its cheaper than ever to fit your home out with a jumbotron screen. (CNN) Quote of the day This is what happens when you mess with the crypto army. Crypto twin Cameron Winklevoss celebrates the victory of blockchain entrepreneur Bernie Moreno, new Senator-elect for Ohio, in a post on X. The big story How covid conspiracies led to an alarming resurgence in AIDS denialism August 2024 Several million people were listening in February when Joe Rogan falsely declared that party drugs were an important factor in AIDS. His guest on The Joe Rogan Experience, the former evolutionary biology professor turned contrarian podcaster Bret Weinstein, agreed with him. Speaking to the biggest podcast audience in the world, the two men were promoting dangerous and false ideasideas that were in fact debunked and thoroughly disproved decades ago. These comments and others like them add up to a small but unmistakable resurgence in AIDS denialisma false collection of theories arguing either that HIV doesnt cause AIDS or that theres no such thing as HIV at all. These claims had largely fallen out of favor until the coronavirus arrived. But, following the pandemic, a renewed suspicion of public health figures and agencies is giving new life to ideas that had long ago been pushed to the margins. Read the full story. Anna Merlan We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Full Moon Matinee is an amazing crime drama resource on YouTube: complete with some excellent acting courtesy of its host. + This is your sign to pick a name and cheer on random strangers during a marathon. I guarantee youll make their day!+ Theres no wrong way to bake a sweet potato, but some ways are better than others.+ Are you a screen creeper? I know I am.

The worlds first barcode, designed in 1948, took more than 25 years to make it out of the lab and onto a retail package. Since then, the barcode has done much more than make grocery checkouts fasterit has remade our understanding of how physical objects can be identified and tracked, creating a new pace and set of expectations for the speed and reliability of modern commerce. Nearly eighty years later, a new iteration of that technology, which encodes data in two dimensions, is poised to take the stage. Todays 2D barcode is not only out of the lab but open to a world of possibility, says Carrie Wilkie, senior vice president of standards and technology at GS1 US. 2D barcodes encode substantially more information than their 1D counterparts. This enables them to link physical objects to a wide array of digital resources. For consumers, 2D barcodes can provide a wealth of product information, from food allergens, expiration dates, and safety recalls to detailed medication use instructions, coupons, and product offers. For businesses, 2D barcodes can enhance operational efficiencies, create traceability at the lot or item level, and drive new forms of customer engagement. DOWNLOAD THE REPORT An array of 2D barcode types supports the information needs of a variety of industries. The GS1 DataMatrix, for example, is used on medication or medical devices, encoding expiration dates, batch and lot numbers, and FDA National Drug Codes. The QR Code is familiar to consumers who have used one to open a website from their phone. Adding a GS1 Digital Link URI to a QR Code enables it to serve two purposes: as both a traditional barcode for supply chain operations, enabling tracking throughout the supply chain and price lookup at checkout, and also as a consumer-facing link to digital information, like expiry dates and serial numbers. Regardless of type, however, all 2D barcodes require a business ecosystem backed by data. To capture new value from advanced barcodes, organizations must supply and manage clean, accurate, and interoperable data around their products and materials. For 2D barcodes to deliver on their potential, businesses will need to collaborate with partners, suppliers, and customers and commit to common data standards across the value chain. Driving the demand for 2D barcodes Shifting to 2D barcodesand enabling the data ecosystems behind themwill require investment by business. Consumer engagement, compliance, and sustainability are among the many factors driving this transition. Real-time consumer engagement: Todays customers want to feel connected to the brands they interact with and purchase from. Information is a key element of that engagement and empowerment. When I think about customer satisfaction, says Leslie Hand, group vice president for IDC Retail Insights, Im thinking about how I can provide more information that allows them to make better decisions about their own lives and the things they buy. 2D barcodes can help by connecting consumers to online content in real time. If, by using a 2D barcode, you have the capability to connect to a consumer in a specific region, or a specific store, and you have the ability to provide information to that consumer about the specific product in their hand, that can be a really powerful consumer engagement tool, says Dan Hardy, director of customer operations for HanesBrands, Inc. 2D barcodes can bring brand and product connectivity directly to an individual consumer, and create an interaction that supports your brand message at an individual consumer/product level. Download the full report. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Reviews editorial staff.

This article is from The Spark, MIT Technology Reviews weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. Voters have elected Donald Trump to a second term in the White House. In the days leading up to the election, I kept thinking about what four years means for climate change right now. Were at a critical moment that requires decisive action to rapidly slash greenhouse-gas emissions from power plants, transportation, industry, and the rest of the economy if were going to achieve our climate goals. The past four years have seen the US take climate action seriously, working with the international community and pumping money into solutions. Now, were facing a period where things are going to be very different. A Trump presidency will have impacts far beyond climate, but for the sake of this newsletter, well stay focused on what four years means in the climate fight as we start to make sense of this next chapter. Joe Biden arguably did more to combat climate change than any other American president. One of his first actions in office was rejoining the Paris climate accordTrump pulled out of the international agreement to fight climate change during his first term in office. Biden then quickly set a new national goal to cut US carbon emissions in half, relative to their peak, by 2030. The Environmental Protection Agency rolled out rules for power plants to slash pollution that harms both human health and the climate. The agency also announced new regulations for vehicle emissions to push the country toward EVs. And the cornerstone of the Biden years has been unprecedented climate investment. A trio of lawsthe Bipartisan Infrastructure Law, the CHIPS and Science Act, and the Inflation Reduction Actpumped hundreds of billions of dollars into infrastructure and research, much of it on climate. Now, this ship is about to make a quick turn. Donald Trump has regularly dismissed the threat of climate change and promised throughout the campaign to counter some of Bidens key moves. We can expect to see a dramatic shift in how the US talks about climate on the international stage. Trump has vowed to once again withdraw from the Paris agreement. Things are going to be weird at the annual global climate talks that kick off next week. We can also expect to see efforts to undo some of Bidens key climate actions, most centrally the Inflation Reduction Act, as my colleague James Temple covered earlier this year. What, exactly, Trump can do will depend on whether Republicans take control of both houses of Congress. A clean sweep would open up more lanes for targeting legislation passed under Biden. (As of sending this email, Republicans have secured enough seats to control the Senate, but the House is uncertain and could be for days or even weeks.) I dont think the rug will be entirely pulled out from under the IRAportions of the investment from the law are beginning to pay off, and the majority of the money has gone to Republican districts. But there will certainly be challenges to pieces, especially the EV tax credits, which Trump has been laser-focused on during the campaign. This all adds up to a very different course on climate than what many had hoped we might see for the rest of this decade. A Trump presidency could add 4 billion metric tons of carbon dioxide emissions to the atmosphere by 2030 over what was expected from a second Biden term, according to an analysis published in April by the website Carbon Brief (this was before Biden dropped out of the race). That projection sees emissions under Trump dropping by 28% below the peak by the end of the decadenowhere near the 50% target set by Biden at the beginning of his term. The US, which is currently the worlds second-largest greenhouse-gas emitter and has added more climate pollution to the atmosphere than any other nation, is now very unlikely to hit Bidens 2030 goal. Thats basically the final nail in the coffin for efforts to limit global warming to 1.5 C (2.7 F) over preindustrial levels. In the days, weeks, and years ahead we'll be coveringwhat this change will mean for efforts to combat climate change and to protect the most vulnerable from the dangerous world were marching towardindeed, already living in. Stay tuned for more from us. Now read the rest of The Spark Related reading Trump wants to unravel Bidens landmark climate law. Read our coverage from earlier this year to see whats most at risk. Its been two years since the Inflation Reduction Act was passed, ushering in hundreds of billions of dollars in climate investment. Read more about the key provisions in this newsletter from August. MIT TECHNOLOGY REVIEW | GETTY Another thing Jennifer Doudna, one of the inventors of the gene-editing tool CRISPR, says the tech could be a major tool to help address climate change and deal with the growing risks of our changing world. The hope is that CRISPRs ability to chop out specific pieces of DNA will make it faster and easier to produce climate-resilient crops and livestock, while avoiding the pitfalls of previous attempts to tweak the genomes of plants and animals. Read the full story from my colleague James Temple. Keeping up with climate Startup Redoxblox is building a technology thats not exactly a thermal battery, but its not not a thermal battery either. The company raised just over $30 million to build its systems, which store energy in both heat and chemical bonds. (Heatmap) Its been a weird fall in the US Northeasta rare drought has brought a string of wildfires, and New York City is seeing calls to conserve water. (New York Times) Its been bumpy skies this week for electric-plane startups. Beta Technologies raised over $300 million in funding, while Lilium may be filing for insolvency soon. (Canary Media) The runway for futuristic electric planes is still a long one. (MIT Technology Review) Metas plan to build a nuclear-powered AI data center has been derailed by a rare species of bee living on land earmarked for the project. (Financial Times) The atmospheric concentration of methanea powerful greenhouse gashas been mysteriously climbing since 2007, and that growth nearly doubled in 2020. Now scientists may have finally figured out the culprits: microbes in wetlands that are getting warmer and wetter. (Washington Post) Greenhouse-gas emissions from the European Union fell by 8% in 2023. The drop is thanks to efforts to shut down coal-fired power plants and generate more electricity from renewables like solar and wind. (The Guardian) Four electric school buses could help officials figure out how to charge future bus fleets. A project in Brooklyn will aim to use onsite renewables and smart charging to control the costs and grid stress of EV charging depots. (Canary Media)

Donald Trumps decisive victory is a stunning setback for climate change. The Republican President-elects return to the White House means the country is going to squander precious momentum, unraveling hard-won policy progress that was just beginning to pay off, all for the second time in less than a decade. It comes at a moment when the world cant afford to waste time, with nations far off track from any greenhouse gas emissions trajectories that would keep our ecosystems stable and our communities safe. Under the policies in place today, the planet is already set to warm by more than 3C in the coming decades. Trump could push the globe into even more dangerous terrain, by defanging President Joe Bidens signature climate laws. In fact, a second Trump administration could boost greenhouse gas emissions by four billion tons through 2030 alone, according to an earlier analysis by Carbon Brief, a well regarded climate news and data site. That will exacerbate the dangers of heat waves, floods, wildfires, droughts, and famine, as well as increase deaths and disease from air pollution, inflicting some $900 million in climate damages around the world, Carbon Brief found. I started as the climate editor at MIT Technology Review just as Trump came into office the last time. Much of the early job entailed covering his systematic unraveling of the modest climate policy and progress that President Barack Obama had managed to achieve. I fear it will be far worse this time, as Trump ambles into office feeling empowered and aggrieved, and ready to test the rule of law and crack down on dissent. This time hell be staffed all the more by loyalists and idealogues, who have already made plans to force out civil servants with expertise and experience across federal agencies, including the Environmental Protection Agency. Hell be backed by a Supreme Court that he moved well to the right, and which has already undercut landmark environmental doctrines and the powers of federal regulatory agencies. This time the setbacks will sting more, too, because the US did finally manage to pass real, substantive climate policy, through the slimmest of congressional margins. The Inflation Reduction Act and Bipartisan Infrastructure Law allocated massive amounts of government funding to accelerate the shift to low-emissions industries and rebuild the US manufacturing base around a clean energy economy. Trump has made clear he will strive to repeal as many of these provisions as he can, tempered perhaps only by Republicans who recognize that these laws are producing revenue and jobs in their districts. Meanwhile, throughout the prolonged presidential campaign, Trump or his surrogates pledged to boost oil and gas production, eliminate federal support for electric vehicles, end power plant pollution rules, and remove the US from the Paris climate agreement yet again. Each of those goals stand in direct opposition to the deep, rapid emissions cuts now necessary toprevent the planet from tipping past higher and higher temperatures. Project 2025, considered a blueprint for the early days of a second Trump administration despite his insistence to the contrary, calls for dismantling or downsizing federal institutions including the the National Oceanic and Atmospheric Administration and the Federal Emergency Management Agency. Any success in doing so threatens to cripple the nations ability to forecast, track, or respond to storms, floods, and fires, similar to those that have devastated communities in recent months. Observers Ive spoken to fear the Trump administration will also revert the Department of Energy, which under Biden had evolved its mission toward developing low-emissions technologies, back to the primary task of helping companies dig up more fossil fuels. The US election could create global ripples as well, and very soon. US negotiators will meet with their counterparts at the annual UN climate conference that kicks off next week. With Trump set to move back into the White House in January, they will have little credibility or leverage to nudge other nations to step up their commitments to reduce emissions. But those are just some of the direct ways that a second Trump administration will enfeeble the nations ability to drive down emissions, and counter the growing dangers of climate change. He also has considerable power to stall the economy and sow international chaos amid a moment of escalating conflicts in Europe and the Middle East. Trumps eagerness to enact tariffs, slash government spending, and deport major portions of the workforce may stunt growth, drive up inflation, and chill investment. All of that would make it far more difficult for companies to raise the capital and purchase the components needed to build anything in the US, whether wind turbines, solar farms, and seawalls, or buildings, bridges, and data centers. President-elect Donald Trump speaks at an election night event in West Palm Beach, Florida. WIN MCNAMEE/GETTY IMAGES His clumsy handling of the economy and international affairs may also help China extend its dominance in producing and selling the components of the energy transition, including batteries, EVs, and solar panels, to customers around the globe. If one job of a commentator is to find some perspective in difficult moments, I admit Im mostly failing in this one. The best I can do is to say that there will be some meaningful lines of defense. For now at least, state leaders and legislatures can continue to enact and implement stronger climate rules. Other nations could step up their efforts to cut emissions and assert themselves as global leaders on climate. The private industry will likely continue to invest in and build businesses in climate tech and clean energy, since solar, wind, batteries and EVs have proven themselves as competitive industries. And technological progress can occur no matter who is sitting in the round room on Pennsylvania Avenue, as researchers continue striving to develop cleaner, cheaper ways of producing our energy, food, and goods. By any measure, the job of addressing climate change is now much harder. Nothing, however, has changed about the stakes. Our world doesnt end if we surpass 2 C, 2.5 C, or even 3 C, but it will steadily become a more dangerous and erratic place. Every tenth of a degree remains worth fighting forwhether in two, four, or a dozen years from nowbecause every bit of warming that nations pull together to prevent eases future suffering somewhere. So as the shock wears off and the despair begins to lift, the core task before us remains the same: to push for progress, whenever, wherever, and however we can.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. OpenAIs Olivier Godement, head of product for its platform, and Romain Huet, head of developer experience, are on a whistle-stop tour around the world. Last week, I sat down with the pair in London before DevDay, the companys annual developer conference. Londons DevDay is the first one for the company outside San Francisco. Godement and Huet are heading to Singapore next. Its been a busy few weeks for the company. In London, OpenAI announced updates to its newRealtime API platform, which allows developers to build voice features into their applications. The company is rolling out new voices and a function that lets developers generate prompts, which will allow them to build apps and more helpful voice assistants more quickly. Meanwhile for consumers, OpenAI announced it was launchingChatGPT search, which allows users to search the internet using the chatbot.Read more here. Both developments pave the way for the next big thing in AI: agents.These are AI assistants that can complete complex chains of tasks, such as booking flights. (You can read my explainer on agents here.) Fast-forward a few yearsevery human on Earth, every business, has an agent. That agent knows you extremely well. It knows your preferences, Godement says. The agent will have access to your emails, apps, and calendars and will act like a chief of staff, interacting with each of these tools and even working on long-term problems, such as writing a paper on a particular topic, he says. OpenAIs strategy is to both build agents itself and allow developers to use its software to build their own agents, says Godement. Voice will play an important role in what agents will look and feel like. At the moment most of the apps are chat based which is cool, but not suitable for all use cases. There are some use cases where youre not typing, not even looking at the screen, and so voice essentially has a much better modality for that, he says. But there are two big hurdles that need to be overcome before agents can become a reality, Godement says. The first is reasoning.Building AI agents requires us to be able to trust that they will be able to complete complex tasks and do the right things, says Huet. Thats where OpenAI reasoning feature comes in.Introducedin OpenAIs o1 model last month, it uses reinforcement learning to teach the model how to process information using chain of thought. Giving the model more time to generate answers allows it to recognize and correct mistakes, break down problems into smaller ones, and try different approaches to answering questions, Godement says. But OpenAIs claims about reasoning should be taken with a pinch of salt, says Chirag Shah, a computer science professor at the University of Washington. Large language models are not exhibiting true reasoning. Its most likely that they have picked up what looks like logic from something theyve seen in their training data. These models sometimes seem to be really amazing at reasoning, but its just like theyre really good at pretending, and it only takes a little bit of picking at them to break them, he says. There is still much more work to be done, Godement admits. In the short term, AI models such as o1 need to be much more reliable, faster, and cheaper. In the long term, the company needs to apply its chain-of-thought technique to a wider pool of use cases. OpenAI has focused on science, coding, and math. Now it wants to address other fields, such as law, accounting, and economics, he says. Second on the to-do list is the ability to connect different tools, Godement says.An AI models capabilities will be limited if it has to rely on its training data alone. It needs to be able to surf the web and look for up-to-date information. ChatGPT search is one powerful way OpenAIs new tools can now do that. These tools need to be able not only to retrieve information but to take actions in the real world. Competitor Anthropic announced a new feature where its Claude chatbot can use a computerby interacting with its interface to click on things, for example. This is an important feature for agents if they are going to be able to execute tasks like booking flights. Godement says o1 can sort of use tools, though not very reliably, and that research on tool use is a promising development. In the next year, Godemont says, he expects the adoption of AI for customer support and other assistant-based tasks to grow.However, he says that it can be hard to predict how people will adopt and use OpenAIs technology. Frankly, looking back every year, Im surprised by use cases that popped up that I did not even anticipate, he says. I expect there will be quite a few surprises that you know none of us could predict. Now read the rest of The Algorithm Deeper Learning This AI-generated version of Minecraft may represent the future of real-time video generation When you walk around in a version of the video game Minecraft from the AI companies Decart and Etched, it feels a little off. Sure, you can move forward, cut down a tree, and lay down a dirt block, just like in the real thing. If you turn around, though, the dirt block you just placed may have morphed into a totally new environment. That doesnt happen in Minecraft. But this new version is entirely AI-generated, so its prone to hallucinations. Not a single line of code was written. Ready, set, go:This version of Minecraft is generated in real time, using a technique known as next-frame prediction. The AI companies behind it did this by training their model, Oasis, on millions of hours of Minecraft game play and recordings of the corresponding actions a user would take in the game. The AI is able to sort out the physics, environments, and controls of Minecraft from this data alone.Read more fromScott J. Mulligan. Bits and Bytes AI search could break the web At its best, AI search can better infer a users intent, amplify quality content, and synthesize information from diverse sources. But if AI search becomes our primary portal to the web, it threatens to disrupt an already precarious digital economy, argues Benjamin Brooks, a fellow at the Berkman Klein Center at Harvard University, who used to lead public policy for Stability AI. (MIT Technology Review)AI will add to the e-waste problem. Heres what we can do about it. Equipment used to train and run generative AI models could produce up to 5 million tons of e-waste by 2030, a relatively small but significant fraction of the global total. (MIT Technology Review)How an interview with a dead luminary exposed the pitfalls of AI A state-funded radio station in Poland fired its on-air talent and brought in AI-generated presenters. But the experiment caused an outcry and was stopped when tone of them interviewed a dead Nobel laureate. (The New York Times)Meta says yes, please, to more AI-generated slopIn Metas latest earnings call, CEO Mark Zuckerberg said were likely to seea whole new category of content, which is AI generated or AI summarized content or kind of existing content pulled together by AI in some way. Zuckerberg added that he thinks thats going to be just very exciting.(404 Media)

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. What do jumping spiders find sexy? How DIY tech is offering insights into the animal mind. Studying the minds of other animals comes with a challenge that human psychologists dont usually face: Your subjects cant tell you what theyre thinking. To get answers from animals, scientists need to come up with creative experiments to learn why they behave the way they do. Sometimes this requires designing and building experimental equipment from scratch. These contraptions can range from ingeniously simple to incredibly complex, but all of them are tailored to help answer questions about the lives and minds of specific species. Do honeybees need a good nights sleep? What do jumping spiders find sexy? Do falcons like puzzles? For queries like these, off-the-shelf gear simply wont do. Check out these contraptions custom-built by scientists to help them understand the lives and minds of the animals they study. Betsy Mason This piece is from the latest print issue of MIT Technology Review, which is all about the weird and wonderful world of food. If you dont already, subscribe to receive future copies once they land. How ChatGPT search paves the way for AI agents Its been a busy few weeks for OpenAI. Alongside updates to its new Realtime API platform, which will allow developers to build apps and voice assistants more quickly, it recently launched ChatGPT search, which allows users to search the internet using the chatbot. Both developments pave the way for the next big thing in AI: agents. These AI assistants can complete complex chains of tasks, such as booking flights. OpenAIs strategy is to both build agents itself and allow developers to use its software to build their own agents, and voice will play an important role in what agents will look and feel like. Melissa Heikkil, our senior AI reporter, sat down with Olivier Godement, OpenAIs head of product for its platform, and Romain Huet, head of developer experience, last week to hear more about the two big hurdles that need to be overcome before agents can become a reality. Read the full story. This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 America is heading to the pollsHeres how Harris and Trump will attempt to lead the US to tech supremacy. (The Information $) + The Stop the Steal election denial movement is preparing to contest the vote. (WP $)+ The muddy final polls suggest its still all to play for. (Vox)2 Abortion rights are on the 2024 ballot A lack of access to basic health care has led to the deaths of at least four women. (NY Mag $)+ Nine states will decide whether to guarantee their residents abortion access. (Fortune)+ If Trump wins he could ban abortion nationwide, even without Congress. (Politico)3 Inside New Yorks election day wargames Tech, business and policy leaders gathered to thrash out potential risks. (WSJ $)+ Violence runs throughout all aspects of this election cycle. (FT $) 4 Elon Musks false and misleading X election posts have billions of views In fact, theyve been viewed twice as much as all Xs political ads this year. (CNN)+ Musks decision to hitch himself to Trump may end up backfiring, though. (FT $)5 Meta will permit the US military to use its AI models Its an interesting update to its previous policy, which explicitly banned its use for military purposes. (NYT $)+ Facebook has kept a low profile during the election cycle. (The Atlantic $)+ Inside the messy ethics of making war with machines. (MIT Technology Review)6 The hidden danger of pirated softwareIts not just viruses you should be worried about. (404 Media) 7 Apple is weighing up expanding into smart glassesWhere Meta leads, Apple may follow. (Bloomberg $) + The coolest thing about smart glasses is not the AR. Its the AI. (MIT Technology Review)8 Indias lithium plans may have been a bit too ambitiousReports of a major lithium reserve appear to have been massively overblown.(Rest of World) + Some countries are ending support for EVs. Is it too soon? (MIT Technology Review)9 Your air fryer could be surveilling you Household appliances are now mostly smart, and stuffed with trackers. (The Guardian)10 How to stay sane during election week Focus on what you can control, and try to let go of what you cant. (WP $)+ Heres how election gurus are planning to cope in the days ahead. (The Atlantic $)+ How to log off. (MIT Technology Review)Quote of the day Were in kind of the throw spaghetti at the wall moment of politics and AI, where this intersection allows people to try new things for propaganda. Rachel Tobac, chief executive of ethical hacking company SocialProof Security, tells the Washington Post why a deepfake video of Martin Luther King endorsing Donald Trump is being shared online in the closing hours of the presidential race. The big story The hunter-gatherer groups at the heart of a microbiome gold rush December 2023 Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisiscasualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimers. Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who dont live in the polluted, processed environment that most of the rest of us share. Theyve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost. But theyre having to navigate an ethical minefield in order to do so. Read the full story.Jessica Hamzelou We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Move over Moo DengHaggis the baby pygmy hippo is the latest internet star! + To celebrate the life of the late, great Quincy Jones, check out this sensational interview in which he spills the beans on everything from the Beatles musical shortcomings to who shot Kennedy. Thank you for the music, Quincy.+ The color of the season? Sage green, apparently.+ Dinosaurs are everywhere, you just need to look for them.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How a breakthrough gene-editing tool will help the world cope with climate change Jennifer Doudna, one of the inventors of the breakthrough gene-editing tool CRISPR, says the technology will help the world grapple with the growing risks of climate change by delivering crops and animals better suited to hotter, drier, wetter, or weirder conditions. The grand hope is that CRISPRs ability to precisely remove specific parts of the DNA within the existing genomes of plants and animals will help avoid many of the pitfalls of earlier adaptation techniques. But there are still considerable obstacles. Last month, Doudna sat down with MIT Technology Review on the sidelines of the Climate & Agriculture Summit at the University of California, Berkeley. Read what she has to say about the future of genetic editing. James Temple Job title of the future: Digital forest ranger When Martin Roth began his career as a forest ranger in the 1980s, his job was to care for the forest in a way that would ensure continuity for decades, even centuries. Now, with climate change, its more about planning for an uncertain future. Roth uses the 3,000 acres of forest along the northeastern shore of Lake Constance in Germany as a testing ground for high-tech solutions to protect nature, earning him the moniker digital forest ranger (Digitalfrster) in the German forestry community. Read the full story.Kaja eruga This piece is from the latest print issue of MIT Technology Review, which is all about the weird and wonderful world of food. If you dont already, subscribe to receive future copies once they land. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Election deniers are already mobilizing on Telegram Poll watchers are poised to dispute votes in Democratic areas, no evidence required. (NYT $)+ TikTok is revealing a major gender divide between the candidates campaigns. (WP $)+ Elon Musk is acting like hes on the ballot himself. (WSJ $)2 Vote-counting staffers are preparing for violent attacks Theyve been trained on how to de-escalate potentially dangerous situations. (The Atlantic $)+ It could be a long, agonizing wait for the final results to be declared. (NY Mag $)+ Elon Musks PAC canvassers are speaking up about their time doorknocking. (Wired $)3 Perplexity wants to prove its trustworthy enough to track election resultsIts a major test for the AI search engine, to say the least. (TechCrunch) + AI-generated search results are often unreliable and open to manipulation. (The Guardian)+ AI search could break the web. (MIT Technology Review)4 The 2024 Presidential campaign has been super surreal From falling out of a coconut tree, to unfounded claims of pet eating. (New Yorker $) 5 This AI supercomputer is funded by OzempicThe financial success of the weight-loss drug made it possible to build Gefion, Denmarks colossal new machine. (WSJ $) + Quantum computing is taking on its biggest challenge: noise. (MIT Technology Review)6 Big Tech is doubling down on its AI spendingTech giants are continuing to sink huge sums into AI development, even if its not making returns yet. (Bloomberg $) + How to fine-tune AI for prosperity. (MIT Technology Review)7 Metas nuclear-powered data center has a bee in its bonnet A rare species of bee is living on the proposed building site. (FT $)8 Touchscreens are out, physical controls are back in Buttons and conventional knobs just get the job done. (IEEE Spectrum)9 Have you checked your privilege lately? Social medias latest wheeze is reminding you how lucky you are. (The Guardian)10 This simple tool will fix your leaky privacy settings Unfortunately, it also comes with a price. (WP $)Quote of the day Id rather work and risk my life to work than stay at home. Waleed Iky, a marketing entrepreneur living in Gaza, explains to the Guardian why he continues to travel to a coworking space with fellow freelancers amid warfare. The big story Whatever happened to DNA computing? October 2021For more than five decades, engineers have shrunk silicon-based transistors over and over again, creating progressively smaller, faster, and more energy-efficient computers in the process. But the long technological winning streakand the miniaturization that has enabled it cant last forever. What could this successor technology be? There has been no shortage of alternative computing approaches proposed over the last 50 years. Read about five of the most memorable ones. Lakshmi Chandrasekaran We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + May these travel posters brighten up your Monday.+ Think you havent got time to exercise? Think againthese workouts take two minutes, no equipment or gym membership needed.+ Uh oh, this Hobbit-o-meter seems to be broken.+ Would you live inside a wind turbine?

Jennifer Doudna, one of the inventors of the breakthrough gene-editing tool CRISPR, says the technology will help the world grapple with the growing risks of climate change by delivering crops and animals better suited to hotter, drier, wetter, or weirder conditions. The potential is huge, says Doudna, who shared the 2020 Nobel Prize in chemistry for her role in the discovery. There is a coming revolution right now with CRISPR. Last month, the Innovation Genomics Institute (IGI), which Doudna founded, hosted the Climate & Agriculture Summit at the University of California, Berkeley, where speakers highlighted the role that genome editing can play in addressing the rising dangers of climate change. Doudna sat down for a brief interview with MIT Technology Review on the sidelines of the closed-door event. She and her coauthors published their landmark paper on the technique in Science 12 years ago, demonstrating that a bacterial immune system could be programmed to locate and snip out specific sections of DNA. The earliest patients have begun receiving the first approved medical treatment created with the genomic scissors, a gene therapy for sickle-cell diseaseand a growing list of foods created with CRISPR are slowly reaching grocery store shelves. Many more CRISPR-edited plants and animals are on the way, and a number of them were altered to promote traits that could help them survive or thrive in conditions fueled by climate change, beginning to fulfill one long-standing promise of genetic engineering. That includes the offspring of two cattle that Acceligen, a Minnesota-based precision breeding business, edited to have shorter coats better suited to hotter temperatures. In 2022, the US Food and Drug Administration determined that meat and other products from those cattle pose low risk to people, animals, the food supply, and the environment and can be marketed for sale to American consumers. Other companies are harnessing CRISPR to develop corn with shorter, stronger stalks that could reduce the loss of crops to increasingly powerful storms; novel cover crops that can help sequester more carbon dioxide and produce biofuels; and animals that could resist zoonotic diseases that climate change may be helping to spread, including avian influenza. For its part, IGI is working to develop rice that can withstand drier conditions, as well as crops that may suck up and store away more carbon dioxide, the principal greenhouse gas driving climate change. Older genetic modification techniques, which involve moving genes from one organism into another, have already delivered agricultural blockbusters, including crops that are resistant to herbicides and corn, potatoes, and soybeans with enhanced protections against pests. The use of such tools to alter crops sparked fears that so-called Frankenfoods would worsen allergies and cause diseases in humans, though these health worries were widely overblown. The grand hope is that CRISPRs ability to precisely remove specific parts of the DNA within the existing genomes of plants and animals will make it faster and easier to create climate-resilient crops and livestock, avoiding many of the pitfalls of earlier breeding and editing techniques. The added promise is that the resulting products may prove more appealing to the public, since they often wont carry DNA from other organismsand wont be labeled as bioengineered. (CRISPR can, however, be used to create such transgenic plants and animals as well.) Its very exciting to see these products coming out, because they have real-world impacts that are incredibly important, especially as were dealing with the changing climate and with our expanding population, says Doudna, a biochemistry professor at the University of California, Berkeley. But there are still considerable obstacles to developing and commercializing transformative new crops and animals, as well as limits to how much the tool may help farmers and communities in regions that become excessively hot, dry, or wet in the coming decades. The coming CRISPRed foods In recent years, the US Department of Agriculture has loosened its rules on governing and labeling genetically modified foods in ways that clear the path for many CRISPR alterations. The department still often oversees and requires disclosures for transgenic plants and animals. But it determined that it will not regulate foods when genome-editing tools like CRISPR are used to make a single modification that could have otherwise been produced through conventional breeding over longer time periods. Were simply providing a trait that could have occurred naturally, Doudna says of the regulatory distinction. Its just that we accelerated that process with CRISPR. The USDA has confirmed to companies or research groups that several dozen crops developed through the use of CRISPR would be exempt from regulation, according to a review of public documents by MIT Technology Review. Harnessing CRISPR and similar technologies will be crucial to feed a growing global population without dramatically expanding the land, fertilizer, and other resources dedicated to farming, says Chavonda Jacobs-Young, the USDAs chief scientist. Jacobs-Young appeared on stage at the UC Berkeley conference and also spoke with MIT Technology Review. We need high-tech tools, she says. Thats going to be an important key to us helping make sure that we have a safe, abundant, delicious and affordable food supply. Chavonda Jacobs-Young, the USDAs chief scientist, and UC Berkeley professor Jennifer Doudna, the UC Berkeley professor who co-developed CRISPR, spoke at the Innovation Genomics Institute's Climate & Agriculture Summit.GLENN RAMIT/INNOVATIVE GENOMICS INSTITUTE Conventional breeding methodswhich include cross-breeding varieties of plants and animals or using radiation or chemicals to create mutationsis a messy process. It can create numerous changes throughout the genome that arent necessarily beneficial, requiring significant trial and error to tease out improvements. The exciting thing with CRISPR for gene editing is you can make changes exactly where you want them, says Emma Kovak, senior food and agriculture analyst at the Breakthrough Institute. Its absolutely huge in terms of saving time and money. As powerful and precise as CRISPR is, however, it still takes considerable work to target the right part of the genome, to evaluate whether any changes provide the hoped-for benefitsand, crucially, to ensure that any edits dont come at the cost of overall plant health or food safety. But improved gene-editing tools have also helped to revive and accelerate research to better understand the complex genomes of plants, which are often several times longer than the human genome. This work is helping scientists identify the genes responsible for relevant traits and the changes that could deliver improvements. Doudna says well see many more crops altered to bolster resilience to climate change as the research in this field progresses. In the future, as we uncover more and more of those fundamental genetics of traits, then CRISPR can come in as a very practical application for creating the kinds of plants that will deal with these oncoming challenges, she says. Practical plants and polite cows IGIs efforts to develop a type of rice that could be more drought tolerant than standard varieties highlight both the promise and challenges ahead. Several research groups have used CRISPR to disable a gene that influences the number of tiny pores in the plants leaves. These pores, known as stomata, allow rice to take in carbon dioxide, emit oxygen, and release water as a means of controlling temperature. The hope is that with fewer stomata, the plants could preserve more water in order to survive and grow in drier conditions. But its proved to be a tricky balancing act. Earlier research efforts knocked out the so-called STOMAGEN gene. That eliminated as much as 80% of pores, which certainly reduced water loss. But it also undermined the plants ability to absorb carbon dioxide and release oxygen, both of which are critical to photosynthesis. IGI researchers zeroed in on a different gene, EPFL10, which had a less dramatic effect, reducing the number of pores by about 20%. According to research that the group published, this tweak helped the plants preserve water but didnt affect its ability to regulate temperatures or exchange gases. It takes plant breeding to the next level, Doudna says of CRISPR. We can adjust the numbers of those pores by dialing up or down certain genes to the levels that actually support plant growth [and] allow farmers to produce rice of the quality and with the yields that they need, but without the loss of water. The organization is also exploring ways that CRISPR could address climate change more directly. That includesa research program aimed at reducing the methane that cattle belch out, which is the primary source of greenhouse-gas emissions related to livestock. IGI is working with researchers at the University of California, Davis, and elsewhere to explore whether CRISPR and other emerging tools could be used to alter microbes in the stomachs of cattle in ways that would reduce their production of the powerful greenhouse gas. A number of research groups and startups are working to reduce those emissions through feed additives, often derived from a type of seaweed. But the hope is that changes to the microbiome of cows could be permanent and inheritable, says Brad Ringeisen, executive director of the IGI. If we succeed, it could potentially be something that could be applicable to nearly every cow in the world, he says. Labeling and safety Kovak says there are still plenty of challenges that could hold up the development of CRISPR-edited animals and plants, including the continuing regulatory obstacles facing products where foreign DNA is introduced or more complicated edits are made. So could the ongoing battles over the intellectual rights to the tool and the variants of it that are emerging, and the costs or burdens that companies must bear to make use of the technology. Doudna herself has been at the center of a messy, bitter, and twisting dispute with the Broad Institute over ownership of the key CRISPR patents. (The Broad is affiliated with MIT, which owns MIT Technology Review.) Each group has secured numerous patents in various countries for certain aspects and varieties of the tool. The continuing legal battles have created complexity and uncertainty for companies hoping to harness CRISPR to develop commercial products. Doudna has founded or cofounded several startups, including Caribou Biosciences, which has sublicensed access to certain CRISPR patents for uses including agriculture. She didnt respond to a follow-up question on this issue before press time. While we have seen a lot of progress in a relatively short time, having the various CRISPR patents controlled by a few entities has at times slowed or stopped some agricultural products from hitting the market, the IGIs Ringeisen said in an email response. But he adds that theres been ongoing progress on discovering and using related gene-editing tools that arent already tied up in patents. Meanwhile, natural-food retailers, skeptics of genetically modified organisms, and others have harshly criticized the USDAs stance on governing and labeling genetically altered foods. They assert that altered crops have had harmful environmental consequences and that the rules dont provide consumers with the transparency they need to make informed choices about the foods they buy and consume. Doudna stresses that it is crucial to use CRISPR and similar tools cautiously. But she says the US has struck the right balance in its approach to regulation and labeling. Its really informed. It really is based on science, she says. Rather than looking at how that plant or crop was created, the question is, What is the final product? She says the IGI has strived to act as a voice of reason on these issues, helping to counter fears and misunderstandings by providing scientific information about how CRISPR can be used to treat human diseases, help farmers adapt to climate change, or address other threats in peoples lives. From the very beginning, of course, it was clear that this was going to be a powerful tool that could be misunderstood and could be misused, she says. But it also has tremendous potential to help us tackle a lot of these challenges.

This article first appeared in The Checkup,MIT Technology Reviewsweekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,sign up here. Over the past month or so, Ive been working on a story about exosomes. You might have seen them advertisedtheyre being touted as a hot new beauty treatment, a fountain of youth, and generally a cure-all therapy for a whole host of ailments. Any cell biologist, though, will tell you what exosomes really are: tiny little blobs that bud off from cells and contain a mixture of proteins and other components. Were not entirely clear what those components are or what they do, despite the promises made by medspas and cosmetic clinics charging thousands of dollars for exosome therapies. As one recipient of an exosome treatment told me, I feel like its a little bit of health marketing bullshit. But there is some very exciting scientific research underway to better understand exactly what exosomes do. Scientists are exploring not only how these tiny particles might help cells communicate, but also how they might be used to diagnose or treat diseases. One company is trying to use exosomes to deliver drugs to the brains of people with rare neurological disorders. It might take longer for these kinds of exosome applications to get to the clinic, but when they do, at least theyll be evidence based. Exosomes are a type of extracellular vesicle. This is a scientific way of saying they are basically little packages that bud off from cells. They were once thought to contain cellular garbage, but now scientists believe they convey important signals between cells and tissues. Exactly what those signals are is still being figured out. The contents of exosomes from cancer cells will probably be somewhat different to those from healthy cells, for example. Because of that, many scientists hope that exosomes could one day be used to help us diagnose diseases. In theory, you could isolate exosomes from a blood sample, examine their contents, and figure out what might be going on in a persons cells. Exosomes might provide clues as to how stressed or close to death a cell is. They might indicate the presence of a tumor. Raghu Kalluri, a cancer biologist at MD Anderson Cancer Center in Houston, is one of the researchers exploring this possibility. I believe that exosomes are likely providing a forensic fingerprint of what the cells are undergoing, he says. But understanding these signals wont be straightforward. Exosomes from cancer cells might send signals to surrounding cells in order to subjugate them into helping the cancer grow, says Kalluri. Cells around a tumor might also send distress signals, alerting the immune system to fight back against it. Theres definitely a role for these exosomes in cancer progression and metastasis, he says. Precisely what [that role is] is an active area of research right now. Exosomes could also be useful for delivering drug treatments. After all, they are essentially little packages of proteins and other matter that can be shuttled between cells. Why not fill them with a medicine and use them to target specific regions of the body? Because exosomes are made in our bodies, they are less likely to be seen as foreign and rejected by our immune systems. And the outer layer of an exosome can serve as a protective coat, shielding the drug from being degraded until it reaches its destination, says James Edgar, who studies exosomes at the University of Cambridge. Its a really attractive method for drug delivery, he says. Dave Carter is one scientist working on it. Carter and his colleagues at Evox Therapeutics in Oxford, UK, are engineering cells to produce compounds that might help treat rare neurological diseases. These compounds could then be released from the cells in exosomes. In their research, Carter and his colleagues can change almost everything about the exosomes they study. They can alter their contents, loading them with proteins or viruses or even gene-editing therapies. They can tweak the proteins on their surfaces to make them target different cells and tissues. They can control how long exosomes stay in an animals circulation. I always used to love playing with Lego, he adds. I feel like Im playing with Lego when Im working with exosomes. Others are hopeful that exosomes themselves hold some kind of therapeutic value. Some hope that exosomes derived from stem cells, for example, might have some regenerative capacity. Ke Cheng at Columbia University in New York is interested in the idea of using exosomes to treat heart and lung conditions. Several preliminary studies suggest that exosomes from heart and stem cells might help animals like mice and pigs recover from heart injuries, such as those caused by a heart attack. There are certainly plenty of clinical trials of exosomes underway. When I searched for exosomes on clinicaltrials.gov, I got over 400 results. These are early-stage trials, howeverand are of variable quality. Still, its an exciting time for exosome research. Its a growing field I think we will see a lot of exciting science in the next five years, says Cheng. Im very optimistic. Now read the rest of The Checkup Read more from MIT Technology Review's archive You can read the piece about the costly exosome treatments being sold in aesthetic clinics and medspas in my longer piece, which was published earlier this week. It can be difficult to establish credibility in a medical field when youre being undercut by clinics selling unapproved treatments and individuals making outlandish claims. Just ask the doctors and scientists trying to legitimize longevity medicine. Some treatments can take off culturally without the backing of rigorous evidence, only to go up in flames when the trial results come in. We saw this earlier this year, when FDA advisors rejected the use of MDMA (or ecstasy) for post-traumatic stress disorder (PTSD) owing to significant confounders in the trials. For some people, unproven treatments might represent a last hope for survival. In those cases, how do we balance access to experimental medicine with the need to protect people who are vulnerable? Stem cells from human embryos promised to launch a medical revolution in which ailing organs and tissues might be repaired when they were isolated just over 25 years ago. So why havent they? From around the web Having a disability shouldnt prevent you from getting married. But thats exactly the conundrum facing some people in the US, as this heartbreaking short documentary shows. (STAT) A Neuralink rival says its eye implant restored vision in blind people. Science Corporations retinal implant enabled some legally blind individuals to read from a book, play cards, and fill out crossword puzzles. (Wired) Women in Texas are dying after doctors delay treating them for miscarriages. Doctors treating Josseli Barnica waited 40 hours for the heart of her fetus to stop beating, despite the fact that miscarriage was inevitable. Her husband says doctors worried that it would be a crime to give her an abortion. She died of a preventable infection three days later. (ProPublica) Between 30% and 50% of twins share a secret language or mode of communication, a phenomenon known as cryptophasia. The Youlden twins call theirs Umeri. (BBC Future) Can a machine express fear? Try your hand at creating AI-generated images frightening enough to spook the machine as part of a project to explore how machines might express humanlike emotions. It is Halloween, after all. (Spook the Machine)