From a fish with a tiny brain to the worlds oldest cheese, we have reported on plenty of strange and unusual science discoveries this year. Challenge yourself and see what you can remember in this fiendish set of questions from our quizmaster Bethan Ackerley

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 is changing how we study bird migration In a warming world, migratory birds face many existential threats. Scientists rely on a combination of methods to track the timing and location of their migrations, but each has shortcomings. And theres another problem: Most birds migrate at night, when its more difficult to identify them visually and while most birders are in bed. For over a century, acoustic monitoring has hovered tantalizingly out of reach as a method that would solve ornithologists woes. Now, finally, machine-learning tools are unlocking a treasure trove of acoustic data for ecologists. Read the full story.Christian Elliot This story is from the forthcoming magazine edition of MIT Technology Review, set to go live on January 6its all about the exciting breakthroughs happening in the world right now. If you dont already, subscribe to receive a copy. A woman in the US is the third person to receive a gene-edited pig kidney Towana Looney, a 53-year-old woman from Alabama, has become the third living person to receive a kidney transplant from a gene-edited pig. Looney, who donated one of her kidneys to her mother back in 1999, developed kidney failure several years later following a pregnancy complication that caused high blood pressure. She started dialysis treatment in December of 2016 and was put on a waiting list for a kidney transplant soon after. But it was difficult to find a match. So Looneys doctors recommended the experimental pig organ as an alternative. After eight years on the waiting list, Looney was authorized to receive the kidney. Read the full story. Jessica Hamzelou Roundtables: The Worst Technology Failures of 2024 Each year, MIT Technology Review publishes a list of the worst technologies of the past 12 months. Antonio Regalado, our senior editor for biomedicine, sat down to discuss 2024s worst failures with our executive editor Niall Firth in a subscriber-exclusive online Roundtable event yesterday. Watch their conversation about what made the cut here, and to make sure you dont miss out in the future, subscribe!MIT Technology Review Narrated: Meet the radio-obsessed civilian shaping Ukraines drone defense Despite it being over 100 years old, radio technology is still critical in almost all aspects of modern warfareincluding in the drones that have come to dominate the Russia-Ukraine war. Serhii Flash Beskrestnov, who has been obsessed with radios since childhood, has become an unlikely hero of the conflict, sharing advice and intel. His work may determine the future of Ukraine, and wars far beyond it. 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 Conspiracy theories are still circulating about those mysterious drones What are they? And where have they come from? (NY Mag $)+ Authorities are attempting to quell public hysteria, but theories abound. (WP $)+ Realistically, theyre probably just standard drones out for a night-time flight. (AP News)2 AI poses a major threat to the power grid Thats according to the US industry watchdog, which is feeling the pressure. (FT $)+ AIs emissions are about to skyrocket even further. (MIT Technology Review)3 SpaceX and Elon Musk are under investigation US federal agencies are probing their repeated failures to comply with reporting rules. (NYT $)4 Nvidia has unveiled a tiny, affordable AI supercomputer Which is handy for roboticists looking to bypass connecting to remote data centers. (Gizmodo)+ While its not the companys most powerful device, its pretty speedy. (WSJ $)+ Microsoft is gobbling up more of Nvidias chips than anyone else. (FT $)+ Blacklisted Chinese AI chip firms gained access to cutting-edge UK tech. (The Guardian) 5 Bitcoins value is rocketing even higherThe industry continues to boom in the wake of Trumps election victory. (Bloomberg $) + So much so, luxury brands are weighing up accepting crypto payments. (Reuters)6 Hepatitis B is an extremely treatable diseaseSo why are so many people still dying from it? (New Yorker $) + Were starting to understand the mysterious surge of hepatitis in children. (MIT Technology Review)7 Earthbrieflyhad an extra second moon And scientists believe it originated from the actual moon we know and love. (New Scientist $) 8 The future of deep-sea miningA set of rules governing how we should do it is highly contentiousand up for debate.(Hakai Magazine) + These deep-sea potatoes could be the future of mining for renewable energy. (MIT Technology Review)9 Resist the temptation to outsource your Christmas shopping to a bot You never know what youll end up with. (Insider $)+ Its probably quicker to browse the web yourself. (WP $)10 Our snacks could soon be designed by AI Confectionary giant Mondelez is using the tech to tweak recipes and test new ones. (WSJ $)+ Forget cookiesthis creamy vegan cheese was made with AI. (MIT Technology Review) Quote of the day It takes a lot for an uber-wealthy, creative-type CEO, many of whom lean left, to suck it up and deal with Trump. But what choice do they have? A Washington lobbyist explains to the Financial Times why the steady stream of tech executives paying their respects to US President-elect Donald Trump shows no sign of slowing. The big story What does GPT-3 know about me? August 2022 One of the biggest stories in tech is the rise of large language models that produce text that reads like a human might have written it. These models power comes from being trained on troves of publicly available human-created text hoovered up from the internet. If youve posted anything even remotely personal in English on the internet, chances are your data might be part of some of the worlds most popular LLMs. Melissa Heikkil, MIT Technology Reviews AI reporter, wondered what data these models might have on herand how it could be misused. So she put OpenAIs GPT-3 to the test. Read about what she found.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.) + 2024 was a seriously weird year, as evidenced by this completely bonkers list.+ Who knew Seal was such a grunge head?+ These Charli xcx Christmas mashups will haunt my dreams forever, and not in a good way.+ Next summer I feel the need to level up my sandcastle game.

AI is all about data. Reams and reams of data are needed to train algorithms to do what we want, and what goes into the AI models determines what comes out. But heres the problem: AI developers and researchers dont really know much about the sources of the data they are using. AIs data collection practices are immature compared with the sophistication of AI model development. Massive data sets often lack clear information about what is in them and where it came from. The Data Provenance Initiative, a group of over 50 researchers from both academia and industry, wanted to fix that. They wanted to know, very simply: Where does the data to build AI come from? They audited nearly 4,000 public data sets spanning over 600 languages, 67 countries, and three decades. The data came from 800 unique sources and nearly 700 organizations. Their findings, shared exclusively with MIT Technology Review, show a worrying trend: AI's data practices risk concentrating power overwhelmingly in the hands of a few dominant technology companies. In the early 2010s, data sets came from a variety of sources, says Shayne Longpre, a researcher at MIT who is part of the project. It came not just from encyclopedias and the web, but also from sources such as parliamentary transcripts, earning calls, and weather reports. Back then, AI data sets were specifically curated and collected from different sources to suit individual tasks, Longpre says. Then transformers, the architecture underpinning language models, were invented in 2017, and the AI sector started seeing performance get better the bigger the models and data sets were. Today, most AI data sets are built by indiscriminately hoovering material from the internet. Since 2018, the web has been the dominant source for data sets used in all media, such as audio, images, and video, and a gap between scraped data and more curated data sets has emerged and widened. In foundation model development, nothing seems to matter more for the capabilities than the scale and heterogeneity of the data and the web, says Longpre. The need for scale has also boosted the use of synthetic data massively. The past few years have also seen the rise of multimodal generative AI models, which can generate videos and images. Like large language models, they need as much data as possible, and the best source for that has become YouTube. For video models, as you can see in this chart, over 70% of data for both speech and image data sets comes from one source. This could be a boon for Alphabet, Googles parent company, which owns YouTube. Whereas text is distributed across the web and controlled by many different websites and platforms, video data is extremely concentrated in one platform. It gives a huge concentration of power over a lot of the most important data on the web to one company, says Longpre. And because Google is also developing its own AI models, its massive advantage also raises questions about how the company will make this data available for competitors, says Sarah Myers West, the coexecutive director at the AI Now Institute. Its important to think about data not as though its sort of this naturally occurring resource, but its something that is created through particular processes, says Myers West. If the data sets on which most of the AI that were interacting with reflect the intentions and the design of big, profit-motivated corporationsthats reshaping the infrastructures of our world in ways that reflect the interests of those big corporations, she says. This monoculture also raises questions about how accurately the human experience is portrayed in the data set and what kinds of models we are building, says Sara Hooker, the vice president of research at the technology company Cohere, who is also part of the Data Provenance Initiative. People upload videos to YouTube with a particular audience in mind, and the way people act in those videos is often intended for very specific effect. Does [the data] capture all the nuances of humanity and all the ways that we exist? says Hooker. Hidden restrictions AI companies dont usually share what data they used to train their models. One reason is that they want to protect their competitive edge. The other is that because of the complicated and opaque way data sets are bundled, packaged, and distributed, they likely dont even know where all the data came from. They also probably dont have complete information about any constraints on how that data is supposed to be used or shared. The researchers at the Data Provenance Initiative found that data sets often have restrictive licenses or terms attached to them, which should limit their use for commercial purposes, for example. This lack of consistency across the data lineage makes it very hard for developers to make the right choice about what data to use, says Hooker. It also makes it almost impossible to be completely certain you havent trained your model on copyrighted data, adds Longpre. More recently, companies such as OpenAI and Google have struck exclusive data-sharing deals with publishers, major forums such as Reddit, and social media platforms on the web. But this becomes another way for them to concentrate their power. These exclusive contracts can partition the internet into various zones of who can get access to it and who cant, says Longpre. The trend benefits the biggest AI players, who can afford such deals, at the expense of researchers, nonprofits, and smaller companies, who will struggle to get access. The largest companies also have the best resources for crawling data sets. This is a new wave of asymmetric access that we havent seen to this extent on the open web, Longpre says. The West vs. the rest The data that is used to train AI models is also heavily skewed to the Western world. Over 90% of the data sets that the researchers analyzed came from Europe and North America, and fewer than 4% came from Africa. "These data sets are reflecting one part of our world and our culture, but completely omitting others," says Hooker. The dominance of the English language in training data is partly explained by the fact that the internet is still over 90% in English, and there are still a lot of places on Earth where theres really poor internet connection or none at all, says Giada Pistilli, principal ethicist at Hugging Face, who was not part of the research team. But another reason is convenience, she adds: Putting together data sets in other languages and taking other cultures into account requires conscious intention and a lot of work. The Western focus of these data sets becomes particularly clear with multimodal models. When an AI model is prompted for the sights and sounds of a wedding, for example, it might only be able to represent Western weddings, because thats all that it has been trained on, Hooker says. This reinforces biases and could lead to AI models that push a certain US-centric worldview, erasing other languages and cultures. We are using these models all over the world, and theres a massive discrepancy between the world were seeing and whats invisible to these models, Hooker says.

A small songbird soars above Ithaca, New York, on a September night. He is one of 4 billion birds, a great annual river of feathered migration across North America. Midair, he lets out what ornithologists call a nocturnal flight call to communicate with his flock. Its the briefest of signals, barely 50 milliseconds long, emitted in the woods in the middle of the night. But humans have caught it nevertheless, with a microphone topped by a focusing funnel. Moments later, software called BirdVoxDetect, the result of a collaboration between New York University, the Cornell Lab of Ornithology, and cole Centrale de Nantes, identifies the bird and classifies it to the species level. Biologists like Cornells Andrew Farnsworth had long dreamed of snooping on birds this way. In a warming world increasingly full of human infrastructure that can be deadly to them, like glass skyscrapers and power lines, migratory birds are facing many existential threats. Scientists rely on a combination of methods to track the timing and location of their migrations, but each has shortcomings. Doppler radar, with the weather filtered out, can detect the total biomass of birds in the air, but it cant break that total down by species. GPS tags on individual birds and careful observations by citizen-scientist birders help fill in that gap, but tagging birds at scale is an expensive and invasive proposition. And theres another key problem: Most birds migrate at night, when its more difficult to identify them visually and while most birders are in bed. For over a century, acoustic monitoring has hovered tantalizingly out of reach as a method that would solve ornithologists woes. In the late 1800s, scientists realized that migratory birds made species-specific nocturnal flight callsacoustic fingerprints. When microphones became commercially available in the 1950s, scientists began recording birds at night. Farnsworth led some of this acoustic ecology research in the 1990s. But even then it was challenging to spot the short calls, some of which are at the edge of the frequency range humans can hear. Scientists ended up with thousands of tapes they had to scour in real time while looking at spectrograms that visualize audio. Though digital technology made recording easier, the perpetual problem, Farnsworth says, was that it became increasingly easy to collect an enormous amount of audio data, but increasingly difficult to analyze even some of it. Then Farnsworth met Juan Pablo Bello, director of NYUs Music and Audio Research Lab. Fresh off a project using machine learning to identify sources of urban noise pollution in New York City, Bello agreed to take on the problem of nocturnal flight calls. He put together a team including the French machine-listening expert Vincent Lostanlen, and in 2015, the BirdVox project was born to automate the process. Everyone was like, Eventually, when this nut is cracked, this is going to be a super-rich source of information, Farnsworth says. But in the beginning, Lostanlen recalls, there was not even a hint that this was doable. It seemed unimaginable that machine learning could approach the listening abilities of experts like Farnsworth. Andrew is our hero, says Bello. The whole thing that we want to imitate with computers is Andrew. They started by training BirdVoxDetect, a neural network, to ignore faults like low buzzes caused by rainwater damage to microphones. Then they trained the system to detect flight calls, which differ between (and even within) species and can easily be confused with the chirp of a car alarm or a spring peeper. The challenge, Lostanlen says, was similar to the one a smart speaker faces when listening for its unique wake word, except in this case the distance from the target noise to the microphone is far greater (which means much more background noise to compensate for). And, of course, the scientists couldnt choose a unique sound like Alexa or Hey Google for their trigger. For birds, we dont really make that choice. Charles Darwin made that choice for us, he jokes. Luckily, they had a lot of training data to work withFarnsworths team had hand-annotated thousands of hours of recordings collected by the microphones in Ithaca. With BirdVoxDetect trained to detect flight calls, another difficult task lay ahead: teaching it to classify the detected calls by species, which few expert birders can do by ear. To deal with uncertainty, and because there is not training data for every species, they decided on a hierarchical system. For example, for a given call, BirdVoxDetect might be able to identify the birds order and family, even if its not sure about the speciesjust as a birder might at least identify a call as that of a warbler, whether yellow-rumped or chestnut-sided. In training, the neural network was penalized less when it mixed up birds that were closer on the taxonomical tree. Last August, capping off eight years of research, the team published a paper detailing BirdVoxDetects machine-learning algorithms. They also released the software as a free, open-source product for ornithologists to use and adapt. In a test on a full season of migration recordings totaling 6,671 hours, the neural network detected 233,124 flight calls. In a 2022 study in the Journal of Applied Ecology, the team that tested BirdVoxDetect found acoustic data as effective as radar for estimating total biomass. BirdVoxDetect works on a subset of North American migratory songbirds. But through few-shot learning, it can be trained to detect other, similar birds with just a few training examples. Its like learning a language similar to one you already speak, Bello says. With cheap microphones, the system could be expanded to places around the world without birders or Doppler radar, even in vastly different recording conditions. If you go to a bioacoustics conference and you talk to a number of people, they all have different use cases, says Lostanlen. The next step for bioacoustics, he says, is to create a foundation model, like the ones scientists are working on for natural-language processing and image and video analysis, that would be reconfigurable for any specieseven beyond birds. That way, scientists wont have to build a new BirdVoxDetect for every animal they want to study. The BirdVox project is now complete, but scientists are already building on its algorithms and approach. Benjamin Van Doren, a migration biologist at the University of Illinois Urbana-Champaign who worked on BirdVox, is using Nighthawk, a new user-friendly neural network based on both BirdVoxDetect and the popular birdsong ID app Merlin, to study birds migrating over Chicago and elsewhere in North and South America. And Dan Mennill, who runs a bioacoustics lab at the University of Windsor, says hes excited to try Nighthawk on flight calls his team currently hand-annotates after theyre recorded by microphones on the Canadian side of the Great Lakes. One weakness of acoustic monitoring is that unlike radar, a single microphone cant detect the altitude of a bird overhead or the direction in which it is moving. Mennills lab is experimenting with an array of eight microphones that can triangulate to solve that problem. Sifting through recordings has been slow. But with Nighthawk, the analysis will speed dramatically. With birds and other migratory animals under threat, Mennill says, BirdVoxDetect came at just the right time. Knowing exactly which birds are flying over in real time can help scientists keep tabs on how species are doing and where theyre going. That can inform practical conservation efforts like Lights Out initiatives that encourage skyscrapers to go dark at night to prevent bird collisions. Bioacoustics is the future of migration research, and were really just getting to the stage where we have the right tools, he says. This ushers us into a new era. Christian Elliott is a science and environmental reporter based in Illinois.

Dual citizen Michael Stiege was raised in Canada but spent many years working in the US.The darkness and cold climate of Canada pushed him to sunny California.For Americans thinking they can simply move up north, it's not that easy, he said.This as-told-to essay is based on a conversation with Michael Stiege, 75, a dual citizen of the US and Canada. Stiege was raised in Canada and spent roughly 30 years working in California before moving back to Canada 15 years ago. He soon plans to split his time between the US and Canada. The conversation was edited for length and clarity.Because I'm a dual citizen of America and Canada, traveling between the two countries is virtually a non-issue.If you're an American coming to Canada, you can travel visa-free. Still, if you're planning to move here and be able to work here, that's another story.You can visit for six months as long as you leave before the end of the six-month period. You can do that back and forth all the time but you won't get access to the social system and healthcare.My friends, who used to live in Chicago, moved to California and said, "We're going to move up to Canada when we retire," butthey couldn't get a visa.This fellow's a Ph.D. and a really smart technical guy and his wife is pretty bright, too. They couldn't get a visa because they were simply too old. Once you're let's say 50 the immigration system disadvantages you. They have a merit-based point system and start worrying about things like age. That's the thinking. Once you reach a certain age, or if you don't have certain other legs up, the criteria by which you can get a working visa is stacked against you.[In Canada's Comprehensive Ranking System (CRS) which rates potential immigrants based on age, language fluency, education, professional expertise, and if you have a Canadian partner applicants 45 years old or older receive 0 points.]Whereas if you're a young guy just out of college, you have some reasonable skills, and you even know a few words of French, you probably wouldn't have a problem.There are ways around it, but if the expectation is, "I'm just going to go up there and apply for a visa and get a visa," it may not happen like that.I needed a change from the cold and long nights in CanadaI was born in Stuttgart, Germany. When my parents and I moved to Canada, I was about 3 and written into my parents' passports.They got their visas and eventually became naturalized Canadians, which was bestowed on me. So, for all practical purposes, I'm a Canadian.I grew up in Toronto, went to school in Toronto, and it wasn't until the early side of my career that I moved out into western Canada to Calgary and British Columbia.I have an engineering degree and an MBA which, at that time, was a pretty good combination to earn a job and make a living. I looked at theI applied to a couple of things and got a call one day. It said, "Are you interested in coming down?" I said yeah, and there I was.I needed warmer weather, and I was able to get rid of Canada's long winter nights. The summers in Canada were great you could golf at 11 p.m. but the winters were awful.Seasonal affective disorder really got to me. It's not so much the cold as the long winter nights. It's dark. My wife says I had started hibernating, so I wanted to leave that behind.I rented in the US and bought a home in CanadaWhen I moved to the US, I found that if I pushed myself, I could've bought a house, but I kept holding off. I found it easy to rent it was affordable. I could get by without any problem. What I didn't put into a mortgage, I put into stocks and stuff like that.I lived there for almost 30 years in two or three residences. I paid about $3,200 monthly in Los Altos Hills, California, right by Stanford University.I came close to buying a couple of times, but the property tax burden in California is significantly higher than what you would find in Canada.If you buy a house in California for $3 million, you're looking at $40,000 yearly in property taxes. [Zillow estimates a $3 million home in Santa Clara County would cost $36,300 annually in property taxes.] I could go on a trip for six months on that.If I did the same thing in Toronto, I might spend between $6,000 and $8,000 and that's a big difference. [According to the city of Toronto, a $3 million home costs $21,459 in city, education, and building fund taxes.]I moved back to Canada about 15 years ago. My father was 96 then, and I said, "Let's go back." My wife is Canadian, and we have family up here. We settled in and bought our house.We have a summer home up north in the lake country. It's not bad, but it gets cold in the winter.If I ever move back to the US, my preference is California.

Staff at major companies have asked their leaders if there are plans to follow Amazon's full return to office.Firms like Meta, Google, and Microsoft have a hybrid setup however, execs say they're eyeing productivity.Research findings on the subject are varied, and the debate will likely continue in 2025.Executives at major companies are referencing a specific term to hedge when asked by employees if they plan to follow in Amazon's footsteps and implement a return to 5 days a week in the office.That word? Productivity.While Amazon has been the most high-profile example this year of a full return to office policy, set to go into effect in January, telecom giant AT&T has also elected to double down on in-person work with a similar 5-day policy, Business Insider first reported.In the wake of Amazon's announcement, executives at both Google and Microsoft, which require employees to be in the office at least 3 days a week, have fielded questions from staff wondering if the days of hybrid work are numbered.Microsoft's executive vice president of cloud and AI, Scott Guthrie, said the company wouldn't change the hybrid work policy unless it noticed a drop in productivity, BI reported in September.In October, Google CEO Sundar Pichai said the company had no plans to order employees back to the office, so long as employees remain productive during their at-home work days, BI previously reported.Over at Meta, Mark Zuckerberg said last year that "early analysis of performance data,"early-career engineers in the office at least 3 days a week. A few months later, the company announced it was requiring employees to return to the office 3 days a week.Executives at Dell called the company's sales team back to the office 5 days a week starting at the end of September, writing in a memo, "Our data shows that sales teams are more productive when onsite."Though Amazon did not explicitly name productivity as a reason for its full return to the office, CEO Andy Jassy emphasized a similar term: effectiveness.Being back in person 5 days a week makes it "easier for our teammates to learn, model, practice, and strengthen our culture; collaborating, brainstorming, and inventing are simpler and more effective; teaching and learning from one another are more seamless; and, teams tend to be better connected to one another," he wrote at the time.For those committing to a full return to office, preparing campuses for the influx of employees in the new year is its own challenge. Amazon has since delayed the announced January 2 effective date of the new mandate for some employees because it doesn't have enough office space in some locations, BI reported earlier this month.As CEOs and company leaders keep an eye on how employees in remote or hybrid setups perform, various studies since the onset of the pandemic have attempted to measure and compare the productivity of employees who work at home and in-office. Research studies have produced conflicting results, further complicated by the matter of how best to define or measure productivity.Goldman Sachs, which has a 5-day-in-office policy, reviewed several analyses that used different ways of evaluating changes in work-from-home productivity, from call-center workers who were randomly chosen to work from home to comparing the productivity of randomly assigned remote workers with their in-office peers.In short, it's hard to say for sure, and executives are deciding what their long-term setup will be after a year in which some of the world's biggest companies put a renewed focus on being "lean" and "efficient."Meanwhile, some employees have returned to commuting in (sometimes "coffee-badging" in and returning home), others have relocated to comply with a policy change, and some have resigned to pursue a hybrid or fully remote opportunity. As companies tighten their belts and conduct layoffs, other workers have taken to workplace forums to wonder if some of the RTO mandates have been a possible "quiet layoffs" tactic.As more major global companies revisit their policies and make changes, CEOs are likely to face more questions on the topic going into the new year.For some, the answer is simple: Stay productive and we'll stay flexible.

A bird flu outbreak has ravaged the world's birds since 2020 and infected cattle earlier this year.California Gov. Gavin Newsom declared a state of emergency over the virus this week.Health officials also confirmed the first "severe" case of and hospitalization for the H5N1 virus.The burgeoning global bird flu outbreak continued its flight path across the country this week, with two major developments that point to the virus's increasingly concerning spread.California Gov. Gavin Newsom declared a state of emergency over the virus on Wednesday, citing a worrying number of infected herds throughout the state in recent months and a need for more resources.Since the state first identified the H5N1 avian influenza virus in cattle in late August, California's agriculture department has confirmed 645 infected dairy herds.Newsom's announcement, meanwhile, came just hours after health officials confirmed the first severe case of bird flu in Louisiana, saying a person was hospitalized with an infection after being exposed to sick birds in his backyard.In recent months, infectious disease experts have grown more and more nervous about the possibility of a human pandemic linked to the virus, even as the Centers for Disease Control and Prevention has maintained that the public health risk for humans is low.Here's where things stand.Bird flu outbreakThe H5N1 virus first reemerged in Europe in 2020 and has since become widespread in birds around the world. The outbreak has killed tens of millions of birds and tens of thousands of sea lions and seals in recent years.Birds carry the disease while migrating and can expose domestic poultry to the virus while never showing signs themselves, according to the CDC.The virus jumped to cattle herds for the first time ever earlier this year in a major escalation. Then, in October, a pig in Oregon tested positive for the virus, an especially concerning case as swine can host both bird and human flu viruses.There has been no known human-to-human transmission yet. Still, the growing pattern of mammal-to-mammal transmission has infectious disease experts on guard against the possibility that H5N1 could eventually become a human pandemic."If it keeps spreading in animals, then it is eventually going to cause problems for humans, either because we don't have food because they've got to start exterminating flocks, or because it starts to make a jump in humans," Dr. Jerome Adams, a former surgeon general and the director of health equity at Purdue University, told Business Insider in April."The more it replicates, the more chances it has to mutate," he added.The ongoing multi-state dairy cattle outbreak, which is believed to have started in Texas, has infected 865 herds across 16 states, according to the CDC, and has led to a growing number of human cases among US dairy and poultry workers.The CDC has thus far confirmed 61 reported human cases and seven probable cases across the US, though some scientists estimate that the real number of infections is higher.More than half of the human cases are tied to interaction with sick cattle. The remaining infections have been traced to exposure to sick poultry or have an unknown origin, the CDC said. The U.S. Department of Agriculture this month issued a federal order that requires the testing of the nation's milk supply. Michael M. Santiago/Getty Images State of emergencyCalifornia's Wednesday announcement will give state and local authorities increased resources to study and contain the outbreak, Newsom said."This proclamation is a targeted action to ensure government agencies have the resources and flexibility they need to respond quickly to this outbreak," the governor said in a statement.Earlier this month, the Agriculture Department said it would start testing the nation's milk supply for traces of the virus, requiring dairy farmers to provide raw milk samples upon request. Up until then, cattle testing for potential infections had been almost entirely voluntary.Dr. Monica Gandhi, a professor of medicine and associate chief of the Division of HIV, Infectious Diseases, and Global Medicine at the University of California, San Francisco, said the declaration will likely give California a greater ability to surveil dairy farms for signs of the virus.But declaring a state of emergency could be a double-edged sword.Phrases "like 'state of emergency,' given that we've just been through a pandemic, can induce panic," Gandhi said.And it's not time to panic yet, she said.Gandhi praised the CDC's "very measured" messaging around the virus thus far and said health officials are closely monitoring the spread.

President-elect Donald Trump is soon to be back in office and grandiose commitments from CEOs sure look poised to return, too. In a Monday briefing alongside SoftBank CEO Masayoshi Son, Trump announced the companys commitment to invest $100 billion in US projects during his second term, with the promise of creating 100,000 new jobs. According to Trump, the new investments by SoftBank, a Japanese tech and telecom company, will focus on artificial intelligence and emerging technologies. If that vow sounds familiar, its because Son offered a similar commitment after Trumps first presidential win in 2016, when Son pledged a $50 billion investment and the creation of 50,000 new jobs. But while SoftBank does seem to have followed through on its investment promise, its unclear that the jobs followed a reminder that splashy announcements like Sons latest should not necessarily be taken as iron-clad guarantees. While CNNs Allison Morrow and David Goldman found that SoftBank did invest roughly $75 billion in US companies after its first pledge, it never made clear how many of those jobs it actually created and how many were actually a result of a new investment, they write.Related:Vox reached out to SoftBank for clarity on its previous investments and how many jobs they generated but did not receive a response prior to publication.Other corporate investments that Trump touted in his first term had underwhelming returns as well. In the case of Foxconn, a Taiwanese manufacturer, for example, the company promised a $10 billion Wisconsin plant and 13,000 jobs, and fell short on both counts. An updated version of the deal eventually saw Foxconn reduce that figure to roughly 1,500 jobs.According to a 2019 ProPublica investigation, multiple other corporations, including Alibaba and Broadcom, were also cited by the Trump administration as sources for new jobs, though many of these gains never materialized. Such pledges, though, still have value to a president who once vowed to run the country like a business, regardless of their eventual success. They provide a good headline for Trump, and a chance to burnish his self-created image as a dealmaker. Now that Trump is returning to power, business leaders are once more looking for ways to build influence with the administration, often with the goal of shaping favorable regulatory outcomes or government contracts. The SoftBank announcement suggests touting prominent job commitments, including those the company might not be able to deliver on, will continue to be one of those avenues. How SoftBanks last commitment panned outSoftBank, which previously owned a large share in the telecom giant Sprint, is known for investing in tech companies via its venture capital fund, the Vision Fund, which is backed in part by the Saudi Arabia and United Arab Emirates sovereign wealth funds. The fund has poured billions into US tech behemoths, including Uber, WeWork, and Slack, including during the first Trump administration. As the New York Times reported in 2019, though, many of these investments were already in the works ahead of Trumps election, and not the result of Sons pledge. And in December 2019, Forbes reporters Biz Carson and Angel Au-Yeung published an investigation into whether those investments created the jobs Son advertised, and were unable to find evidence corroborating job creation on the promised scale. SoftBank would not provide an estimate of how many jobs it has created in the U.S. since Sons pledge, they wrote. Because the majority of the Vision Funds investments have gone to private companies, public data is not available, making it hard to hold Son accountable for his promise. Carson and Au-Yeung also contacted 50 SoftBank-backed companies to inquire about new jobs they had added, with many declining to comment, while others reported only marginal gains. The 2019 ProPublica report reached a similar conclusion, noting that SoftBanks investments had resulted in roughly 10,200 new or saved jobs at that point in time, meaning it wasnt on pace to generate 50,000 jobs by the end of Trumps term. Publicly available information about some of the companies in which SoftBank invested also suggests that it may have struggled to reach the job creation benchmark it set. Some of the larger firms it backed, like Uber and WeWork, for example, oversaw wide-ranging layoffs which affected thousands of employees in 2019 and 2020. And a number of other startups that SoftBank funded were much smaller, so there was less potential for establishing new jobs at a large scale. During Trumps first term, SoftBanks investment and jobs announcement came as the administration was poised to oversee a possible T-Mobile merger with Sprint, which the Justice Department and Federal Communications Commission ultimately approved. This year, it comes as Trump weighs tariffs on goods from a number of US trading partners including Japan, where SoftBank is headquartered. SoftBanks example, as well as the slew of CEOs including Apples Tim Cook and Amazons Jeff Bezos recently traveling to meet with Trump, suggest the president-elects hold over big business is as strong as ever. But while announcements about new factories, billion-dollar investments, and spectacular job creation sound impressive, the results from Trumps first term suggest the reality likely wont match the promises that are made. Youve read 1 article in the last monthHere at Vox, we're unwavering in our commitment to covering the issues that matter most to you threats to democracy, immigration, reproductive rights, the environment, and the rising polarization across this country.Our mission is to provide clear, accessible journalism that empowers you to stay informed and engaged in shaping our world. By becoming a Vox Member, you directly strengthen our ability to deliver in-depth, independent reporting that drives meaningful change.We rely on readers like you join us.Swati SharmaVox Editor-in-ChiefSee More: Politics

President-elect Donald Trumps contempt for the media is well-known, but two lawsuits filed against news organizations offer a worrying look at the next four years for outlets and reporters covering his administration.Disney, the parent company of ABC News, settled a suit with Trump for $15 million; Trump sued the company because anchor George Stephanopoulos mistakenly said Trump was found liable for raping writer E. Jean Carroll, when he was actually found liable for sexual abuse. Trump also sued the Des Moines Register, an Iowa newspaper, this week because they published a poll showing Vice President Kamala Harris would win the state; he also sued the person who produced the poll. Trump is alleging this is election interference. These developments come amid ongoing lawsuits Trump has against CBS and publisher Simon & Schuster.These kinds of lawsuits arent new. Theyre meant to be expensive and time-consuming for news companies, even if the outlets win the case. They are also meant to make all news organizations question whether its worth publishing critical reporting about public figures in this case, Trump given the financial, legal, and public relations risk.The US has strong protections for the press, so news groups can fulfill their obligation to inform the public, particularly about powerful people and organizations. But Trumps lawsuits could interfere with their ability to do so.Lawsuits such as Trumps against ABC, the Des Moines Register, and the Iowa pollster Ann Selzer are commonly called strategic litigation against public participation (SLAPP) suits. The first such suit Trump filed was a defamation case against ABC News. Trumps team initially filed the suit in Florida in the spring, after Stephanopoulos said in a March interview with Rep. Nancy Mace (R-SC) on This Week that Trump was found to have raped Carroll in 1996. In fact, the jury in Carrolls case found in 2023 that Trumps actions qualified as sexual abuse, and not rape under the law in New York, where the Carroll case was filed. However, the judge in the case did note that Trumps abuse did align with commonly held definitions of rape, even if they didnt meet the specific legal standard.Defamation cases against the press must meet a very high standard in the US; reporters make mistakes, but thats not enough to warrant a lawsuit against a reporter or news organization. Defamation cases must prove a reporter acted with actual malice, writing or saying something they knew or had good reason to believe was false. In July, Disney asked to have the suit dropped, on the grounds that Stephanopouloss statements were essentially true, if imprecise, and his reporting was protected by Florida law. The judge argued that a jury could potentially find Stephanopoulos guilty. Then on Friday, she ordered Stephanopoulos and Trump into depositions and for Disney to hand over documents related to the case. Disney reportedly pushed to settle the case in part because the company worried it could lose a jury trial in heavily Republican Florida.In Iowa, Trump is suing the Des Moines Register, its parent company Gannett, Selzer, and her polling company on the grounds that they perpetrated consumer fraud for producing and publishing a pre-election poll that had Vice President Kamala Harris winning the state. (Trump won Iowa by over 10 percentage points.) The lawsuit accuses Selzer of brazen election interference, according to the New York Times. Trump filed a similar suit against CBS News in October, alleging that an interview with Harris on its program 60 Minutes violated consumer protection laws due to its editing.SLAPP suits are meant to have a chilling effectThe sort of lawsuits Trump is filing against media companies are the latest workaround that wealthy and powerful people who want to bully the press have found to attempt to circumvent the well-established safeguards for the press under the First Amendment against defamation and similar claims, Seth Stern, director of advocacy at the Freedom of the Press Foundation, told Vox. Trump may not win these suits, but thats not really the point. What really marks a SLAPP suit, aside from it being legally baseless, is that the intent is not so much to win, but to send a message to bully and punish critics through forcing them to incur legal fees, and not only legal fees, but time costs spent defending against litigation, which can be quite devastating for smaller outlets, Stern said. Trump has made clear in the past he knows the purpose of these suits to induce these costs, and to establish fear of speaking out against him. As Trump infamously said about a lawsuit he brought against the author of a book he did not like, I spent a couple of bucks on legal fees, and they spent a whole lot more. I did it to make his life miserable, which Im happy about.SLAPP suits have a long history in the US, according to Samantha Barbas, a legal historian at the University of Iowa School of Law.Historically, politicians and other public figures have tried to shut down their critics in the press using defamation law in particular, she told Vox. Back in the early 20th century, it was really common for public officials to basically try to sue the press out of existence over comments they didnt like.Now, the US has robust press freedom protections, established in the 1964 case New York Times v. Sullivan, which codified those protections. Many states also have anti-SLAPP legislation, and a federal anti-SLAPP law was proposed in 2022. But Trump has said he wants to undo some of those safeguards. That those protections exist largely because of Supreme Court precedent rather than due to federal law is reportedly also part of why Disneys lawyers chose to settle so the case couldnt go to the Supreme Court and potentially result in a rollback of Sullivan. At least one Supreme Court justice, Justice Thomas has expressed skepticism about the New York Times v. Sullivan standard, and would like the Supreme Court to revisit it, Stern said, although theres no indication the other justices share Thomas opinion. For not, there is nothing stopping Trump from continuing to file SLAPP suits and he may even inspire copycat cases, Barbas said.When someone wins a libel suit against the press, it will just inspire others to bring claims, and it becomes very dangerous, Barbas said.Youve read 1 article in the last monthHere at Vox, we're unwavering in our commitment to covering the issues that matter most to you threats to democracy, immigration, reproductive rights, the environment, and the rising polarization across this country.Our mission is to provide clear, accessible journalism that empowers you to stay informed and engaged in shaping our world. By becoming a Vox Member, you directly strengthen our ability to deliver in-depth, independent reporting that drives meaningful change.We rely on readers like you join us.Swati SharmaVox Editor-in-ChiefSee More:

The Supreme Court issued an unusual order on Wednesday morning, announcing it will hear a case deciding the fate of TikTok on a fast-tracked schedule. The case, known as TikTok v. Garland, asks whether a federal law potentially banning TikTok, which President Joe Biden signed in April, violates the First Amendment. The law would ban the short-form video app, which is owned by Chinese tech company ByteDance, within the United States unless ByteDance sells the platform to a different owner before January 19. The law was upheld by a lower federal court earlier this month, and so a ban may be imminent unless the Supreme Court intervenes.The Supreme Courts order announcing it will hear TikTok v. Garland departs from the Courts ordinary procedures in several ways, compressing both the briefing schedule for this case, and the amount of time the justices will have to consider the case after briefing is completed.The Courts order instructs TikTok and the Justice Department, as well as other parties challenging the law, including a number of content creators who use the platform, to all file their briefs simultaneously on December 27, two days after Christmas. The justices will hear oral arguments on January 10.It is likely that the Court is following this unusually fast schedule typically, a case waits months for an oral argument before the justices, even after the Court announces it will hear that case because the justices want to issue their final decision before the ban takes effect on January 19.Although TikTok raised several constitutional challenges to the law, known as the Protecting Americans from Foreign Adversary Controlled Applications Act, the Supreme Courts review will focus on a single question: Whether this law, which could shut down one of the most popular online platforms in the country, violates the free speech clause of the First Amendment.TikTok pits national security concerns against free speech protectionsThe law targeting TikTok passed both houses of Congress with broad support from both political parties. The laws supporters justify such an unusual encroachment on traditional free speech protections because they fear the Chinese government will either use TikTok to gather data on Americans, or they will manipulate the content that appears on TikTok to shape US opinion.The question of just how much control China can and does exercise over TikTok is hotly contested. TikToks parent company, ByteDance, is based in Beijing. Like many Chinese companies, it is legally required to host an in-house Communist Party committee composed of TikTok employees who are also party members.The law at issue in the case bans internet hosting services and other tech companies including Apple and Google, whose app stores make TikTok available to download from serving foreign adversary controlled applications. While other apps can potentially qualify as such an application, the law specifically states that TikTok, as well as any other application operated by ByteDance, qualifies. TikTok can potentially escape this ban if it is sold to another company that is not controlled by a foreign adversary, but no sale appears imminent.A federal appeals court upheld this law earlier in December, essentially arguing that national security concerns trump free speech concerns. While that opinion includes many details about the sheer volume of data controlled by TikTok, it included far less evidence than courts normally provide when upholding laws burdening free speech that the governments stated interest in protecting national security justifies this particular law.The appeals court justified this approach by arguing that judgments of the Congress and the Executive regarding the national security threat posed by the TikTok platform is entitled to significant weight.The lower court is correct that courts often defer to the other branches in matters of national security, and it cites Supreme Court precedents establishing that general proposition. But the amount of deference shown by the lower court in this case is unusual. All three appeals court judges who heard this case agreed that the TikTok ban should receive heightened scrutiny from the judiciary because it threatens free speech. Laws that are subject to such scrutiny are presumptively unconstitutional, and the government bears the burden of proving that such a law can be justified.As the Supreme Court said in Ashcroft v. ACLU (2004), when there are substantial factual disputes regarding whether a law burdening free speech can be justified by some other compelling national need, the Government must shoulder its full constitutional burden of proof.Which isnt to say that the Justice Department cannot overcome that burden in this case, if it can produce sufficient evidence that China will use TikTok to undermine US national security. But, under existing precedent, the government must provide that evidence if it wants this law to survive.In any event, we will likely know more about what sort of evidence the Justice Department plans to muster in defense of this law after it files its brief on December 27 although its worth noting that the government could potentially file some of this information under seal if it would require them to disclose classified information, as seems possible given the national security concerns alleged by the government.For now, the only thing that appears certain about this case is that the justices are moving very quickly and one way or another, the future of TikTok will likely be resolved before the federal ban takes effect in January.Youve read 1 article in the last monthHere at Vox, we're unwavering in our commitment to covering the issues that matter most to you threats to democracy, immigration, reproductive rights, the environment, and the rising polarization across this country.Our mission is to provide clear, accessible journalism that empowers you to stay informed and engaged in shaping our world. By becoming a Vox Member, you directly strengthen our ability to deliver in-depth, independent reporting that drives meaningful change.We rely on readers like you join us.Swati SharmaVox Editor-in-ChiefSee More: