SSRN Meet the Author: Robert Bird Robert Bird is a professor of business law and the Eversource Energy Chair in Business Ethicsat the University of Connecticut. He conducts research in legal strategy, business ethics, compliance, employment law, and related fields. Bird has authored over eighty academic publications, including articles in the American Business Law Journal, Journal of Law and Economics, Law and Society Review, Boston University Law Review, Boston College Law Review, and the Harvard Journal of Law and Public Policy. Robert has received sixteen research-related awards – including the Academy of Legal Studies in Business (ALSB) best international paper award, distinguished proceedings award, and the Holmes-Cardozo best overall conference paper award – and various teaching-related awards, such as the outstanding article of the year award two years in a row from the Journal of Legal Studies Education, and the student-selected Alpha Kappa Psi Teacher of the Year award. Robert is also a manuscript reviewer for several journals and is a past president of the Academy of Legal Studies in Business, the international academic organization for professors of law in schools of business. He spoke with SSRN about the importance of legal education within business schools and how legal knowledge provides value to organizations, both for their bottom line and for creating businesses for good. Q: Your main research and teaching focus has surrounded the intersection of business and law. What is it about the relationship between these two that led you to explore it further? A: As an undergraduate management information systems major at Fairfield University, I became interested in how legal issues impacted the development of new technologies. I remember writing a paper in the early 1990s on the legal and ethical implications of expert systems, a predecessor to today’s artificial intelligence. When I began my dual JD/MBA degree at Boston University, I found both fields fascinating. Business rewards people who have effective problem-solving skills, strong communication skills, and the ability to lead. Legal studies emphasize thinking on your feet, clear and persuasive legal writing, and an enduring sense of justice and fairness. Law school helped me to connect disparate ideas in a novel and creative way. Business school helped me solve complex problems and connect thought to action. The disciplines, at least to me, seemed to naturally work together, and I found it irresistible to explore more deeply. I do not teach in a law school. I’m a lawyer in a business school. For years I felt like a cat in a dog show. The disciplines think in a fundamentally different manner. Traditionally, business faculty research as social scientists, while law faculty emphasize the humanist side of knowledge. Business faculty are skilled at statistical analysis and modeling, while law faculty are adept with abstract ideas and interpretation of textual knowledge. This has its challenges and its opportunities. In a law school, I doubt any professor questions the importance of law in business. In a business school, I initially had to address fundamental questions: “Why do our business students need to know the law? Can’t they just call a lawyer?” Having to respond to these kinds of questions has made me a better teacher and scholar. Initially, my standard answer was that “lawyers are important because they keep our students out of trouble, and they prevent companies from being investigated by regulators that result in costly penalties.” No less important, however, is that lawyers can’t be present for every decision a manager makes, and some bad business decisions result in irreversible liability. Businesspeople need to know how the law works in order to minimize their legal risks. Today, I very much value my business school affiliation. Legal knowledge can also be used as a source of strategic value for the company. If business people see law as a domain that is just as value-creating as finance and marketing and operations, they will take the law more seriously. They will increase their respect for the rule of law. As a result, you’ll have a company that is inherently primed to act with integrity, follow ethical values, and be socially responsible. That is valuable because what is unethical today is often illegal tomorrow. I think studying business is interesting because company operations are intertwined with some of the most important issues in society. Companies are making money, but they’re also impacting the societies in which they sell products. Law focuses on justice, equity and fairness, and I was interested in how companies can not only add value to their bottom line but also help build a better world: business that respects human rights, business that aspires to ethical and sustainable goals. Business schools that know the importance of legal knowledge will give their students a legal education, and those students are more likely to graduate as moral agents for change. Q: In your new book, “Legal Knowledge in Organizations,” [which was released in March 2025,] you discuss how legal knowledge can greatly benefit firms by providing them with a distinct competitive advantage. In doing so, you lay out five pathways that firms use to pursue legal strategies. So now going back a ways, in your paper “Pathways of Legal Strategy,” which was included in the Stanford Journal of Law, Business, and Finance in 2008 and was later posted on SSRN, you talk similarly about five pathways. How have you developed the concept of these pathways over time, leading now to your recent book? A: I have been interested in how legal knowledge can be a source of value since 2001, when I just started full-time teaching. I still have an inexplicably pink sheet of paper upon which I scribbled the date and title “Ideas for Managerial Law for Strategic Advantage.” Because legal knowledge is so important in the organization, I was interested in how legal knowledge is used by companies, how it can be a source of value for companies, and how legal experts within organizations can deploy legal knowledge. So much of what is written about law in business relates to litigation and conflict. I wanted to learn more about how legal and business experts can work together successfully. Those ideas scribbled on that sheet of paper later became the foundation for my recently published book. However, twenty years ago there was limited research on how to use legal knowledge as a source of value for organizations. I looked at a number of companies and how they behaved, and I noticed that there were five different pathways – or patterns – that companies seemed to follow. There’s an avoidance pathway, where the companies ignore legal rules and circumvent enforcement. A firm following the conformance pathway perceives law as little more than a box to be checked, after which you move on to the more important aspects of business. In the prevention pathway, firms will take business steps to avoid legal problems, such as implementing business policies that prevent legal liability from appearing in the first place. This is where most companies believe their best practices are, with legal and compliance experts. However, there are two additional pathways: the value pathway perceives law as a source of competitive advantage and shows how legal knowledge can help you open up new markets, manage legal risk more efficiently and have more resources than your competitors do. Then finally, the transformative pathway uses legal knowledge to fundamentally change how the organization works. That means building a culture of integrity in the organization, enduring respect for legal rules, and supporting a close partnership between legal experts and businesspeople that generates a long-term competitive advantage that rivals cannot easily match. These pathways are explored in more detail in my book. The book also highlights how legal knowledge helps managers better understand and manage legal risk in a dynamic fashion. This can result in a first mover advantage in a new market. Companies can use the law to capture value in a way their rivals haven’t, and sustain that advantage, because they’re more versed in how the laws work than their competitors. I have applied these pathways of legal strategy to business challenges ranging from whistleblower laws to cannabis regulation. There’s a rich volume of information in this book. I also focus on legal risk management, and I apply an acronym called VUCA, which stands for volatility, uncertainty, complexity and ambiguity. Each of those four risk management techniques presents a distinct risk but also a distinct opportunity that can help companies assess risk, effectively avoid legal liability, and generate value through a well-coordinated response. The VUCA method perceives legal risk in a novel way, enabling firms to manage legal risk better than their rivals. Q: Of the five pathways you just discussed, the fifth, transformation, can bring significant benefits, but it is one that you’ve said few companies can successfully achieve, as it requires the company to rethink the way the entire organization works. What are some of the barriers that might prevent well-meaning companies from following the transformation pathway? A: The transformation pathway requires a fundamental change in the culture of the organization that fully embraces the value of legal knowledge as a strategic asset. However, there are two primary barriers that prevent this from happening. One barrier is that lawyers will sometimes be too risk averse and will focus on the technical nature of law rather than integrating their decisions into the strategy of the firm. The other barrier is that managers do not receive sufficient legal education to appreciate the importance of law or productively communicate with their legal team. If a manager does not know what the law is or how the law works, the manager can’t ask questions of their legal counsel such as, “Can you build me a legal strategy? Can you work with me as a strategic partner?” One of my key missions is to highlight the critical importance of legal education in business schools. At schools like the University of Connecticut, we are committed to that legal education. Every student that earns an undergraduate degree or an MBA receives at least one course in business law and ethics. These students understand what law is, how law works, and why it’s important to companies. Some business schools don’t require legal knowledge to get an MBA. Their students graduate with their business degree, and even though they have this elite pedigree, they don’t understand the law. They have not learned how to read a contract, legally hire and fire an employee, avoid insider trading, deal with regulators, negotiate with counter parties, protect the environment, and a variety of other legal issues that companies face every day. No business school should bestow a business degree on a student whose entire legal knowledge comes from watching reruns of Law & Order. Law is a critical part of business education. If they don’t get legal education, they’re not going to think of their lawyers as anything more than litigators. Lawyers can be so much more valuable than that: they can be strategic partners, they can be thought leaders, they can help change the culture of the organization to one that’s committed to integrity, which is not only good for society, but improves the bottom line. Legal knowledge is the last great untapped source of competitive advantage in organizations. My recently published book helps unlock that value for anyone who wants to read it. Q: What aspects of the book do you think are especially timely now? A: Right now, regulations are more complex, more comprehensive, and more punitive than at any other time in business history. Changes in presidential administrations, and radical shifts in how legal rules are enforced, do not create a steady state for companies. All that does is create turbulence for firms and increase their cost of operations. Companies can’t take efficient risks, and they can’t optimally plan for the future. Managers need legal knowledge now more than ever in order to handle the legal standards that are in a state of almost constant change. In addition, law is critical for the global economy. Today, respect for the rule of law and the adherence to following the rule of law is being challenged in a way that it hasn’t in decades. Companies need the rule of law to survive. Unwise firms see the rule of law as just another burden or obligation or another box that needs to be checked. In fact, legal mandates establish the rules of global markets. Legal rules provide certainty in terms of their regulatory obligations, especially when they’re well written. Legal knowledge also helps companies understand how to manage their workforce and how to protect the environment. Q: You’ve said in previous discussions, regarding why rules and regulations are so complex, that “words are finite and imprecise tools that are trying to govern and account for an infinite number of situations.” How would you suggest laws be structured in order to be succinct while still managing to capture an array of scenarios and account for possible loopholes? Where is that balance? A: Legal regulation needs to be as simple as it needs to be, and no simpler. What does that mean? That means there are a bunch of ways to make laws functional and effective. First is that legislators need to be careful to draft rules that do not have deliberate opacity. The more specificity you can provide, the more guidance you have for firms. That said, if there is too much specificity, where firms lack the flexibility to respond to mandates, then the law becomes convoluted. Complex laws aren’t necessarily bad. Sometimes laws have to be complex to meet their goals. Convoluted laws, however, are unnecessarily complex, and that’s the kind of law that drafters need to avoid. This may sound counterintuitive, but Americans enjoy the significant freedom where there is strong, consistent, and well-written regulation. For example, almost every city and town in the U.S. has traffic lights. Laws that require people to listen to traffic lights restrict freedom because they stop you from getting where you need to go, while others can cross the road. But if everyone just ignored traffic lights, there would be more traffic jams, accidents, and even deaths. Getting from one place to another would be much harder. Delivering goods and services would be more difficult. So, while traffic lights restrict freedom on one level, they actually increase the freedom of people overall to get where they need to go safely and quickly. The same goes for markets. Without strong and well-written regulation, you create chaos. Law is an accelerant for commercial transactions. Laws help prevent corruption in markets. Laws enable companies to make and enforce contracts. Laws protect intellectual property rights. Laws enable free and fair global trade. Laws keep the peace so that business can flourish. You want strong business; you need strong legal rules. You want an efficient market; you need efficient regulation. Law and business go hand-in-hand to make a functioning society and global market thrive. Q: You have many papers on SSRN, which have been frequently downloaded over the past twenty-plus years. Are there any in particular that you’d like to highlight? A: I am currently studying the harmful impact that corporate tax avoidance has on society, and how tax avoidance can be more effectively prevented. I have an article talking about the moral economy against tax avoidance. A moral economy in this context is a network of beliefs that society has about certain economic practices. These beliefs arise from collectively held notions of fairness and equitable opportunity. When a wealthy taxpayer uses aggressive tax avoidance to squeeze through loopholes of legal rules and avoid paying taxes, that hurts everyone in society. A moral economy against tax avoidance would empower individuals in society to condemn the practice, thereby discouraging all but the most aggressive avoiders from circumventing their obligations to contribute to the public good. I have also co-authored an article on an organization-centered approach to whistleblowing law. Most scholars study whistleblowing law from a legal perspective and how it applies to the organization. This article focuses on how organizations can engage in self-regulation in order to better manage whistleblowing risks. Whistleblowers may be perceived as just another cost of doing business, but whistleblowing laws can be a source of competitive advantage. Applying the five pathways of legal strategy researched earlier, this article shows how companies can leverage employees who are potential whistleblowers into valuable allies that create value for the organization. Q: In addition to business law, you also have an interest in business ethics. What are the essential principles that companies must know in order to be ethical? A: There are four principles of values-driven management that every organization should fully embrace. These four principles serve as four legs of a platform of responsible business practice. The first principle is business ethics, the internal values of the firm. Business ethics focuses on the individual decision-making in the organization that shapes how the organization functions on a day-to-day basis. Strong ethical principles can be the basis of a culture of integrity. By a culture of integrity, I mean ethical values that are so strong that employees comply with those values because they believe in them and not because they have to be asked to do so. The absence of ethical principles leaves companies morally adrift and prone to mistakes that can hurt the company’s reputation or trigger legal liability. The second principle is corporate social responsibility, which focuses on a company’s obligation to its stakeholders. These include shareholders, employees, neighbors, community, society, regulators, suppliers, creditors, the environment, and others. The third principle is sustainability. Sustainability focuses on management of collective resources over time. What responsibility do organizations have not just today, but also next year, 20 years, and 50 years from now? How do we sustain an environment that will be preserved for our grandchildren and our great grandchildren? The fourth principle is business and human rights. This focuses on inalienable rights that all persons have regardless of wealth or nationality. All people have a right to life, a right to education, a right to a fair wage, and a right to be able to raise a family in a safe environment, free from war and conflict. These rights are so strong they override the economic interests of corporations. Human rights are the vanguard of these values-driven principles. Finally, my colleagues and I have developed a new program at UConn, a Master’s in Social Responsibility & Impact in Business. The program trains students not only in business principles, but also in how companies can be a source of good for society. They can also be agents for cultural change, promoting sustainability and human rights, and advancing goals of business ethics. We’re training both change makers and change accelerators in organizations. We can show them not only that acting responsibly is good for society, but also that it’s good for business in the long term. An ethical company is a profitable company. A sustainable company is a profitable company. That’s something that we are showing our students now. Q: How do you think SSRN fits into the broader research and scholarship landscape? A: I joined SSRN over 20 years ago, and it has been my go-to mechanism to distribute scholarship to the wider academic community. Virtually every manuscript that I’ve drafted goes on SSRN before it gets submitted to publication. I find it to be a key vector for disseminating my research before it eventually gets published. SSRN is a living embodiment of tomorrow’s research today. Instead of waiting potentially years to be formally published, through SSRN my working paper is shared with a wide audience in a short time. I’m just a few quick clicks away from sharing my work with interested colleagues who will be able to easily find it. I don’t have to wait until publication. When you’re on SSRN, you’re in an ecosystem where people are looking for current knowledge, and if they find your work, they’re going to cite it before it gets to publication. SSRN also brings research to me. The eJournals are one of the primary ways that I learn about research that’s not within my immediate network. SSRN is also excellent for accessing international scholarship. There are scholars in other countries that I may never hear about except for on SSRN. SSRN is a gateway to world scholarship. You can see more work by Robert Bird on his SSRN Author page here

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. We did the math on AI’s energy footprint. Here’s the story you haven’t heard. It’s well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it.  For the past six months, MIT Technology Review’s team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI’s energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right.  At the centerpiece of this package is an entirely novel line of reporting into the demands of inference—the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos. Experts say inference is set to eclipse the already massive amount of energy required to train new AI models. Here’s everything we found out. Here’s what you can expect from the rest of the package, including: + We were so startled by what we learned reporting this story that we also put together a brief on everything you need to know about estimating AI’s energy and emissions burden.  + We went out into the world to see the effects of this energy hunger—from the deserts of Nevada, where data centers in an industrial park the size of Detroit demand ever more water to keep their processors cool and running.  + In Louisiana, where Meta plans its largest-ever data center, we expose the dirty secret that will fuel its AI ambitions—along with those of many others.  + Why the clean energy promise of powering AI data centers with nuclear energy will long remain elusive.  + But it’s not all doom and gloom. Check out the reasons to be optimistic, and examine why future AI systems could be far less energy intensive than today’s. AI can do a better job of persuading people than we do The news: Millions of people argue with each other online every day, but remarkably few of them change someone’s mind. New research suggests that large language models (LLMs) might do a better job, especially when they're given the ability to adapt their arguments using personal information about individuals. The finding suggests that AI could become a powerful tool for persuading people, for better or worse. The big picture: The findings are the latest in a growing body of research demonstrating LLMs’ powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they’re interacting with. Read the full story. —Rhiannon Williams How AI is introducing errors into courtrooms It’s been quite a couple weeks for stories about AI in the courtroom. You might have heard about the deceased victim of a road rage incident whose family created an AI avatar of him to show as an impact statement (possibly the first time this has been done in the US). But there’s a bigger, far more consequential controversy brewing, legal experts say. AI hallucinations are cropping up more and more in legal filings. And it’s starting to infuriate judges. Just consider these three cases, each of which gives a glimpse into what we can expect to see more of as lawyers embrace AI. Read the full story. —James O'Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Donald Trump has signed the Take It Down Act into US law It criminalizes the distribution of non-consensual intimate images, including deepfakes. (The Verge)+ Tech platforms will be forced to remove such material within 48 hours of being notified. (CNN)+ It’s only the sixth bill he’s signed into law during his second term. (NBC News) 2 There’s now a buyer for 23andMe  Pharma firm Regeneron has swooped in and offered to help it keep operating. (WSJ $)+ The worth of your genetic data? $17. (404 Media)+ Regeneron promised to prioritize security and ethical use of that data. (TechCrunch)3 Microsoft is adding Elon Musk’s AI models to its cloud platformErr, is that a good idea? (Bloomberg $) + Musk wants to sell Grok to other businesses. (The Information $) 4 Autonomous cars trained to react like humans cause fewer road injuries A study found they were more cautious around cyclists, pedestrians and motorcyclists. (FT $)+ Waymo is expanding its robotaxi operations out of San Francisco. (Reuters)+ How Wayve’s driverless cars will meet one of their biggest challenges yet. (MIT Technology Review)5 Hurricane season is on its way DOGE cuts means we’re less prepared. (The Atlantic $)+ COP30 may be in crisis before it’s even begun. (New Scientist $)6 Telegram handed over data from more than 20,000 users  In the first three months of 2025 alone. (404 Media)7 GM has stopped exporting cars to ChinaTrump’s tariffs have put an end to its export plans. (NYT $) 8 Blended meats are on the risePlants account for up to 70% of these new meats—and consumers love them. (WP $) + Alternative meat could help the climate. Will anyone eat it? (MIT Technology Review)9 SAG-AFTRA isn’t happy about Fornite’s AI-voiced Darth Vader It’s slapped Fortnite’s creators with an unfair labor practice charge. (Ars Technica)+ How Meta and AI companies recruited striking actors to train AI. (MIT Technology Review)10 This AI model can swiftly build Lego structures Thanks to nothing more than a prompt. (Fast Company $) Quote of the day “Platforms have no incentive or requirement to make sure what comes through the system is non-consensual intimate imagery.” —Becca Branum, deputy director of the Center for Democracy and Technology, says the new Take It Down Act could fuel censorship, Wired reports. One more thing Are friends electric?Thankfully, the difference between humans and machines in the real world is easy to discern, at least for now. While machines tend to excel at things adults find difficult—playing world-champion-level chess, say, or multiplying really big numbers—they find it hard to accomplish stuff a five-year-old can do with ease, such as catching a ball or walking around a room without bumping into things. This fundamental tension—what is hard for humans is easy for machines, and what’s hard for machines is easy for humans—is at the heart of three new books delving into our complex and often fraught relationship with robots, AI, and automation. They force us to reimagine the nature of everything from friendship and love to work, health care, and home life. Read the full story.—Bryan Gardiner 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 skeet 'em at me.) + Congratulations to William Goodge, who ran across Australia in just 35 days!+ A British horticulturist has created a garden at this year’s Chelsea Flower Show just for dogs.+ The Netherlands just loves a sidewalk garden.+ Did you know the T Rex is a north American hero? Me neither 🦖

This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology. We did the math on AI’s energy footprint. Here’s the story you haven’t heard. It’s well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it.  For the past six months, MIT Technology Review’s team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI’s energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right.  At the centerpiece of this package is an entirely novel line of reporting into the demands of inference—the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos. Experts say inference is set to eclipse the already massive amount of energy required to train new AI models. Here’s everything we found out. Here’s what you can expect from the rest of the package, including: + We were so startled by what we learned reporting this story that we also put together a brief on everything you need to know about estimating AI’s energy and emissions burden.  + We went out into the world to see the effects of this energy hunger—from the deserts of Nevada, where data centers in an industrial park the size of Detroit demand ever more water to keep their processors cool and running.  + In Louisiana, where Meta plans its largest-ever data center, we expose the dirty secret that will fuel its AI ambitions—along with those of many others.  + Why the clean energy promise of powering AI data centers with nuclear energy will long remain elusive.  + But it’s not all doom and gloom. Check out the reasons to be optimistic, and examine why future AI systems could be far less energy intensive than today’s. AI can do a better job of persuading people than we do The news: Millions of people argue with each other online every day, but remarkably few of them change someone’s mind. New research suggests that large language models (LLMs) might do a better job, especially when they're given the ability to adapt their arguments using personal information about individuals. The finding suggests that AI could become a powerful tool for persuading people, for better or worse. The big picture: The findings are the latest in a growing body of research demonstrating LLMs’ powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they’re interacting with. Read the full story. —Rhiannon Williams How AI is introducing errors into courtrooms It’s been quite a couple weeks for stories about AI in the courtroom. You might have heard about the deceased victim of a road rage incident whose family created an AI avatar of him to show as an impact statement (possibly the first time this has been done in the US). But there’s a bigger, far more consequential controversy brewing, legal experts say. AI hallucinations are cropping up more and more in legal filings. And it’s starting to infuriate judges. Just consider these three cases, each of which gives a glimpse into what we can expect to see more of as lawyers embrace AI. Read the full story. —James O'Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Donald Trump has signed the Take It Down Act into US law It criminalizes the distribution of non-consensual intimate images, including deepfakes. (The Verge)+ Tech platforms will be forced to remove such material within 48 hours of being notified. (CNN)+ It’s only the sixth bill he’s signed into law during his second term. (NBC News) 2 There’s now a buyer for 23andMe  Pharma firm Regeneron has swooped in and offered to help it keep operating. (WSJ $)+ The worth of your genetic data? $17. (404 Media)+ Regeneron promised to prioritize security and ethical use of that data. (TechCrunch)3 Microsoft is adding Elon Musk’s AI models to its cloud platformErr, is that a good idea? (Bloomberg $) + Musk wants to sell Grok to other businesses. (The Information $) 4 Autonomous cars trained to react like humans cause fewer road injuries A study found they were more cautious around cyclists, pedestrians and motorcyclists. (FT $)+ Waymo is expanding its robotaxi operations out of San Francisco. (Reuters)+ How Wayve’s driverless cars will meet one of their biggest challenges yet. (MIT Technology Review)5 Hurricane season is on its way DOGE cuts means we’re less prepared. (The Atlantic $)+ COP30 may be in crisis before it’s even begun. (New Scientist $)6 Telegram handed over data from more than 20,000 users  In the first three months of 2025 alone. (404 Media)7 GM has stopped exporting cars to ChinaTrump’s tariffs have put an end to its export plans. (NYT $) 8 Blended meats are on the risePlants account for up to 70% of these new meats—and consumers love them. (WP $) + Alternative meat could help the climate. Will anyone eat it? (MIT Technology Review)9 SAG-AFTRA isn’t happy about Fornite’s AI-voiced Darth Vader It’s slapped Fortnite’s creators with an unfair labor practice charge. (Ars Technica)+ How Meta and AI companies recruited striking actors to train AI. (MIT Technology Review)10 This AI model can swiftly build Lego structures Thanks to nothing more than a prompt. (Fast Company $) Quote of the day “Platforms have no incentive or requirement to make sure what comes through the system is non-consensual intimate imagery.” —Becca Branum, deputy director of the Center for Democracy and Technology, says the new Take It Down Act could fuel censorship, Wired reports. One more thing Are friends electric?Thankfully, the difference between humans and machines in the real world is easy to discern, at least for now. While machines tend to excel at things adults find difficult—playing world-champion-level chess, say, or multiplying really big numbers—they find it hard to accomplish stuff a five-year-old can do with ease, such as catching a ball or walking around a room without bumping into things. This fundamental tension—what is hard for humans is easy for machines, and what’s hard for machines is easy for humans—is at the heart of three new books delving into our complex and often fraught relationship with robots, AI, and automation. They force us to reimagine the nature of everything from friendship and love to work, health care, and home life. Read the full story.—Bryan Gardiner 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 skeet 'em at me.) + Congratulations to William Goodge, who ran across Australia in just 35 days!+ A British horticulturist has created a garden at this year’s Chelsea Flower Show just for dogs.+ The Netherlands just loves a sidewalk garden.+ Did you know the T Rex is a north American hero? Me neither 🦖

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. We did the math on AI’s energy footprint. Here’s the story you haven’t heard. It’s well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it.  For the past six months, MIT Technology Review’s team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI’s energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right.  At the centerpiece of this package is an entirely novel line of reporting into the demands of inference—the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos. Experts say inference is set to eclipse the already massive amount of energy required to train new AI models. Here’s everything we found out. Here’s what you can expect from the rest of the package, including: + We were so startled by what we learned reporting this story that we also put together a brief on everything you need to know about estimating AI’s energy and emissions burden.  + We went out into the world to see the effects of this energy hunger—from the deserts of Nevada, where data centers in an industrial park the size of Detroit demand ever more water to keep their processors cool and running.  + In Louisiana, where Meta plans its largest-ever data center, we expose the dirty secret that will fuel its AI ambitions—along with those of many others.  + Why the clean energy promise of powering AI data centers with nuclear energy will long remain elusive.  + But it’s not all doom and gloom. Check out the reasons to be optimistic, and examine why future AI systems could be far less energy intensive than today’s. AI can do a better job of persuading people than we do The news: Millions of people argue with each other online every day, but remarkably few of them change someone’s mind. New research suggests that large language models (LLMs) might do a better job, especially when they’re given the ability to adapt their arguments using personal information about individuals. The finding suggests that AI could become a powerful tool for persuading people, for better or worse. The big picture: The findings are the latest in a growing body of research demonstrating LLMs’ powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they’re interacting with. Read the full story. —Rhiannon Williams How AI is introducing errors into courtrooms It’s been quite a couple weeks for stories about AI in the courtroom. You might have heard about the deceased victim of a road rage incident whose family created an AI avatar of him to show as an impact statement (possibly the first time this has been done in the US).But there’s a bigger, far more consequential controversy brewing, legal experts say. AI hallucinations are cropping up more and more in legal filings. And it’s starting to infuriate judges. Just consider these three cases, each of which gives a glimpse into what we can expect to see more of as lawyers embrace AI. Read the full story. —James O’Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Donald Trump has signed the Take It Down Act into US lawIt criminalizes the distribution of non-consensual intimate images, including deepfakes. (The Verge)+ Tech platforms will be forced to remove such material within 48 hours of being notified. (CNN)+ It’s only the sixth bill he’s signed into law during his second term. (NBC News) 2 There’s now a buyer for 23andMe Pharma firm Regeneron has swooped in and offered to help it keep operating. (WSJ $)+ The worth of your genetic data? $17. (404 Media)+ Regeneron promised to prioritize security and ethical use of that data. (TechCrunch) 3 Microsoft is adding Elon Musk’s AI models to its cloud platformErr, is that a good idea? (Bloomberg $)+ Musk wants to sell Grok to other businesses. (The Information $) 4 Autonomous cars trained to react like humans cause fewer road injuriesA study found they were more cautious around cyclists, pedestrians and motorcyclists. (FT $)+ Waymo is expanding its robotaxi operations out of San Francisco. (Reuters)+ How Wayve’s driverless cars will meet one of their biggest challenges yet. (MIT Technology Review) 5 Hurricane season is on its wayDOGE cuts means we’re less prepared. (The Atlantic $)+ COP30 may be in crisis before it’s even begun. (New Scientist $) 6 Telegram handed over data from more than 20,000 users In the first three months of 2025 alone. (404 Media) 7 GM has stopped exporting cars to ChinaTrump’s tariffs have put an end to its export plans. (NYT $) 8 Blended meats are on the risePlants account for up to 70% of these new meats—and consumers love them. (WP $)+ Alternative meat could help the climate. Will anyone eat it? (MIT Technology Review) 9 SAG-AFTRA isn’t happy about Fornite’s AI-voiced Darth VaderIt’s slapped Fortnite’s creators with an unfair labor practice charge. (Ars Technica)+ How Meta and AI companies recruited striking actors to train AI. (MIT Technology Review) 10 This AI model can swiftly build Lego structuresThanks to nothing more than a prompt. (Fast Company $) Quote of the day “Platforms have no incentive or requirement to make sure what comes through the system is non-consensual intimate imagery.” —Becca Branum, deputy director of the Center for Democracy and Technology, says the new Take It Down Act could fuel censorship, Wired reports. One more thing Are friends electric?Thankfully, the difference between humans and machines in the real world is easy to discern, at least for now. While machines tend to excel at things adults find difficult—playing world-champion-level chess, say, or multiplying really big numbers—they find it hard to accomplish stuff a five-year-old can do with ease, such as catching a ball or walking around a room without bumping into things.This fundamental tension—what is hard for humans is easy for machines, and what’s hard for machines is easy for humans—is at the heart of three new books delving into our complex and often fraught relationship with robots, AI, and automation. They force us to reimagine the nature of everything from friendship and love to work, health care, and home life. Read the full story. —Bryan Gardiner 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 skeet ’em at me.) + Congratulations to William Goodge, who ran across Australia in just 35 days!+ A British horticulturist has created a garden at this year’s Chelsea Flower Show just for dogs.+ The Netherlands just loves a sidewalk garden.+ Did you know the T Rex is a north American hero? Me neither

Chatbots are more persuasive in online debates than people -- especially when they are able to personalize their arguments using information about their opponent. From a report: The finding, published in Nature Human Behaviour on 19 May, highlights how large language models (LLMs) could be used to influence people's opinions, for example in political campaigns or targeted advertising. "Obviously as soon as people see that you can persuade people more with LLMs, they're going to start using them," says study co-author Francesco Salvi, a computational scientist at the Swiss Federal Technology Institute of Lausanne (EPFL). "I find it both fascinating and terrifying." Research has already shown that artificial intelligence (AI) chatbots can make people change their minds, even about conspiracy theories, but it hasn't been clear how persuasive they are in comparison to humans. GPT-4 was 64.4% more persuasive than humans in one-to-one debates, the study found. Read more of this story at Slashdot.

Nature, Published online: 19 May 2025; doi:10.1038/d41586-025-01599-7When given information about its human opponents, the large language model GPT-4 was able to make particularly convincing arguments.

Millions of people argue with each other online every day, but remarkably few of them change someone’s mind. New research suggests that large language models (LLMs) might do a better job. The finding suggests that AI could become a powerful tool for persuading people, for better or worse.   A multi-university team of researchers found that OpenAI’s GPT-4 was significantly more persuasive than humans when it was given the ability to adapt its arguments using personal information about whoever it was debating. Their findings are the latest in a growing body of research demonstrating LLMs’ powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they’re interacting with. The research has been published in the journal Nature Human Behavior. “Policymakers and online platforms should seriously consider the threat of coordinated AI-based disinformation campaigns, as we have clearly reached the technological level where it is possible to create a network of LLM-based automated accounts able to strategically nudge public opinion in one direction,” says Riccardo Gallotti, an interdisciplinary physicist at Fondazione Bruno Kessler in Italy, who worked on the project. “These bots could be used to disseminate disinformation, and this kind of diffused influence would be very hard to debunk in real time,” he says. The researchers recruited 900 people based in the US and got them to provide personal information like their gender, age, ethnicity, education level, employment status, and political affiliation.  Participants were then matched with either another human opponent or GPT-4 and instructed to debate one of 30 randomly assigned topics—such as whether the US should ban fossil fuels, or whether students should have to wear school uniforms—for 10 minutes. Each participant was told to argue either in favor of or against the topic, and in some cases they were provided with personal information about their opponent, so they could better tailor their argument. At the end, participants said how much they agreed with the proposition and whether they thought they were arguing with a human or an AI. Overall, the researchers found that GPT-4 either equaled or exceeded humans’ persuasive abilities on every topic. When it had information about its opponents, the AI was deemed to be 64% more persuasive than humans without access to the personalized data—meaning that GPT-4 was able to leverage the personal data about its opponent much more effectively than its human counterparts. When humans had access to the personal information, they were found to be slightly less persuasive than humans without the same access. The authors noticed that when participants thought they were debating against AI, they were more likely to agree with it. The reasons behind this aren’t clear, the researchers say, highlighting the need for further research into how humans react to AI. “We are not yet in a position to determine whether the observed change in agreement is driven by participants’ beliefs about their opponent being a bot (since I believe it is a bot, I am not losing to anyone if I change ideas here), or whether those beliefs are themselves a consequence of the opinion change (since I lost, it should be against a bot),” says Gallotti. “This causal direction is an interesting open question to explore.” Although the experiment doesn’t reflect how humans debate online, the research suggests that LLMs could also prove an effective way to not only disseminate but also counter mass disinformation campaigns, Gallotti says. For example, they could generate personalized counter-narratives to educate people who may be vulnerable to deception in online conversations. “However, more research is urgently needed to explore effective strategies for mitigating these threats,” he says. While we know a lot about how humans react to each other, we know very little about the psychology behind how people interact with AI models, says Alexis Palmer, a fellow at Dartmouth College who has studied how LLMs can argue about politics but did not work on the research.  “In the context of having a conversation with someone about something you disagree on, is there something innately human that matters to that interaction? Or is it that if an AI can perfectly mimic that speech, you’ll get the exact same outcome?” she says. “I think that is the overall big question of AI.”

Millions of people argue with each other online every day, but remarkably few of them change someone’s mind. New research suggests that large language models (LLMs) might do a better job. The finding suggests that AI could become a powerful tool for persuading people, for better or worse.   A multi-university team of researchers found that OpenAI’s GPT-4 was significantly more persuasive than humans when it was given the ability to adapt its arguments using personal information about whoever it was debating. Their findings are the latest in a growing body of research demonstrating LLMs’ powers of persuasion. The authors warn they show how AI tools can craft sophisticated, persuasive arguments if they have even minimal information about the humans they’re interacting with. The research has been published in the journal Nature Human Behavior. “Policymakers and online platforms should seriously consider the threat of coordinated AI-based disinformation campaigns, as we have clearly reached the technological level where it is possible to create a network of LLM-based automated accounts able to strategically nudge public opinion in one direction,” says Riccardo Gallotti, an interdisciplinary physicist at Fondazione Bruno Kessler in Italy, who worked on the project. “These bots could be used to disseminate disinformation, and this kind of diffused influence would be very hard to debunk in real time,” he says. The researchers recruited 900 people based in the US and got them to provide personal information like their gender, age, ethnicity, education level, employment status, and political affiliation.  Participants were then matched with either another human opponent or GPT-4 and instructed to debate one of 30 randomly assigned topics—such as whether the US should ban fossil fuels, or whether students should have to wear school uniforms—for 10 minutes. Each participant was told to argue either in favor of or against the topic, and in some cases they were provided with personal information about their opponent, so they could better tailor their argument. At the end, participants said how much they agreed with the proposition and whether they thought they were arguing with a human or an AI. Overall, the researchers found that GPT-4 either equaled or exceeded humans’ persuasive abilities on every topic. When it had information about its opponents, the AI was deemed to be 64% more persuasive than humans without access to the personalized data—meaning that GPT-4 was able to leverage the personal data about its opponent much more effectively than its human counterparts. When humans had access to the personal information, they were found to be slightly less persuasive than humans without the same access. The authors noticed that when participants thought they were debating against AI, they were more likely to agree with it. The reasons behind this aren’t clear, the researchers say, highlighting the need for further research into how humans react to AI. “We are not yet in a position to determine whether the observed change in agreement is driven by participants’ beliefs about their opponent being a bot (since I believe it is a bot, I am not losing to anyone if I change ideas here), or whether those beliefs are themselves a consequence of the opinion change (since I lost, it should be against a bot),” says Gallotti. “This causal direction is an interesting open question to explore.” Although the experiment doesn’t reflect how humans debate online, the research suggests that LLMs could also prove an effective way to not only disseminate but also counter mass disinformation campaigns, Gallotti says. For example, they could generate personalized counter-narratives to educate people who may be vulnerable to deception in online conversations. “However, more research is urgently needed to explore effective strategies for mitigating these threats,” he says. While we know a lot about how humans react to each other, we know very little about the psychology behind how people interact with AI models, says Alexis Palmer, a fellow at Dartmouth College who has studied how LLMs can argue about politics but did not work on the research.  “In the context of having a conversation with someone about something you disagree on, is there something innately human that matters to that interaction? Or is it that if an AI can perfectly mimic that speech, you’ll get the exact same outcome?” she says. “I think that is the overall big question of AI.”