Technology shapes relationships. Relationships shape technology.

Greetings from a cold winter day.

As I write this letter, we are in the early stages of President Donald Trump’s second term. The inauguration was exactly one week ago, and already an image from that day has become an indelible symbol of presidential power: a photo of the tech industry’s great data barons seated front and center at the swearing-in ceremony.

Elon Musk, Sundar Pichai, Jeff Bezos, and Mark Zuckerberg all sat shoulder to shoulder, almost as if on display, in front of some of the most important figures of the new administration. They were not the only tech leaders in Washington, DC, that week. Tim Cook, Sam Altman, and TikTok CEO Shou Zi Chew also put in appearances during the president’s first days back in action. 

These are tycoons who lead trillion-dollar companies, set the direction of entire industries, and shape the lives of billions of people all over the world. They are among the richest and most powerful people who have ever lived. And yet, just like you and me, they need relationships to get things done. In this case, with President Trump. 

Those tech barons showed up because they need relationships more than personal status, more than access to capital, and sometimes even more than ideas. Some of those same people—most notably Zuckerberg—had to make profound breaks with their own pasts in order to forge or preserve a relationship with the incoming president. 

Relationships are the stories of people and systems working together. Sometimes by choice. Sometimes for practicality. Sometimes by force. Too often, for purely transactional reasons. 

That’s why we’re exploring relationships in this issue. Relationships connect us to one another, but also to the machines, platforms, technologies, and systems that mediate modern life. They’re behind the partnerships that make breakthroughs possible, the networks that help ideas spread, and the bonds that build trust—or at least access. In this issue, you’ll find stories about the relationships we forge with each other, with our past, with our children (or not-quite-children, as the case may be), and with technology itself. 

Rhiannon Williams explores the relationships people have formed with AI chatbots. Some of these are purely professional, others more complicated. This kind of relationship may be novel now, but it’s something we will all take for granted in just a few years. 

Also in this issue, Antonio Regalado delves into our relationship with the ecological past and the way ancient DNA is being used not only to learn new truths about who we are and where we came from but also, potentially, to address modern challenges of climate and disease.

In an extremely thought-provoking piece, Jessica Hamzelou examines people’s relationships with the millions of IVF embryos in storage. Held in cryopreservation tanks around the world, these embryos wait in limbo, in ever growing numbers, as we attempt to answer complicated ethical and legal questions about their existence and preservation. 

Turning to the workplace, Rebecca Ackermann explores how our relationships with our employers are often mediated through monitoring systems. As she writes, what may be more important than the privacy implications is how the data they collect is “shifting the relationships between workers and managers” as algorithms “determine hiring and firing, promotion and ‘deactivation.’” Good luck with that.

Thank you for reading. As always, I value your feedback. So please, reach out and let me know what you think. I really don’t want this to be a transactional relationship. 

Warmly,

Mat Honan
Editor in Chief
mat.honan@technologyreview.com

The foundations of America’s prosperity are being dismantled

Ever since World War II, the US has been the global leader in science and technology—and benefited immensely from it. Research fuels American innovation and the economy in turn. Scientists around the world want to study in the US and collaborate with American scientists to produce more of that research. These international collaborations play a critical role in American soft power and diplomacy. The products Americans can buy, the drugs they have access to, the diseases they’re at risk of catching—are all directly related to the strength of American research and its connections to the world’s scientists.

That scientific leadership is now being dismantled, according to more than 10 federal workers who spoke to MIT Technology Review, as the Trump administration—spearheaded by Elon Musk’s Department of Government Efficiency (DOGE)—slashes personnel, programs, and agencies. Meanwhile, the president himself has gone after relationships with US allies.   

These workers come from several agencies, including the Departments of State, Defense, and Commerce, the US Agency for International Development, and the National Science Foundation. All of them occupy scientific and technical roles, many of which the average American has never heard of but which are nevertheless critical, coordinating research, distributing funding, supporting policymaking, or advising diplomacy.

They warn that dismantling the behind-the-scenes scientific research programs that backstop American life could lead to long-lasting, perhaps irreparable damage to everything from the quality of health care to the public’s access to next-generation consumer technologies. The US took nearly a century to craft its rich scientific ecosystem; if the unraveling that has taken place over the past month continues, Americans will feel the effects for decades to come. 

Most of the federal workers spoke on condition of anonymity because they were not authorized to talk or for fear of being targeted. Many are completely stunned and terrified by the scope and totality of the actions. While every administration brings its changes, keeping the US a science and technology leader has never been a partisan issue. No one predicted the wholesale assault on these foundations of American prosperity.

“If you believe that innovation is important to economic development, then throwing a wrench in one of the most sophisticated and productive innovation machines in world history is not a good idea,” says Deborah Seligsohn, an assistant professor of political science at Villanova University who worked for two decades in the State Department on science issues. “They’re setting us up for economic decline.”

The biggest funder of innovation

The US currently has the most top-quality research institutes in the world. This includes world-class universities like MIT (which publishes MIT Technology Review) and the University of California, Berkeley; national labs like Oak Ridge and Los Alamos; and federal research facilities run by agencies like the National Oceanic and Atmospheric Administration and the Department of Defense. Much of this network was developed by the federal government after World War II to bolster the US position as a global superpower. 

Before the Trump administration’s wide-ranging actions, which now threaten to slash federal research funding, the government remained by far the largest supporter of scientific progress. Outside of its own labs and facilities, it funded more than 50% of research and development across higher education, according to data from the National Science Foundation. In 2023, that came to nearly $60 billion out of the $109 billion that universities spent on basic science and engineering. 

The return on these investments is difficult to measure. It can often take years or decades for this kind of basic science research to have tangible effects on the lives of Americans and people globally, and on the US’s place in the world. But history is littered with examples of the transformative effect that this funding produces over time. The internet and GPS were first developed through research backed by the Department of Defense, as was the quantum dot technology behind high-resolution QLED television screens. Well before they were useful or commercially relevant, the development of neural networks that underpin nearly all modern AI systems was substantially supported by the National Science Foundation. The decades-long drug discovery process that led to Ozempic was incubated by the Department of Veterans Affairs and the National Institutes of Health. Microchips. Self-driving cars. MRIs. The flu shot. The list goes on and on. 

In her 2013 book The Entrepreneurial State, Mariana Mazzucato, a leading economist studying innovation at University College London, found that every major technological transformation in the US, from electric cars to Google to the iPhone, can trace its roots back to basic science research once funded by the federal government. If the past offers any lesson, that means every major transformation in the future could be shortchanged with the destruction of that support.

The Trump administration’s distaste for regulation will arguably be a boon in the short term for some parts of the tech industry, including crypto and AI. But the federal workers said the president’s and Musk’s undermining of basic science research will hurt American innovation in the long run. “Rather than investing in the future, you’re burning through scientific capital,” an employee at the State Department said. “You can build off the things you already know, but you’re not learning anything new. Twenty years later, you fall behind because you stopped making new discoveries.”

A global currency

The government doesn’t just give money, either. It supports American science in numerous other ways, and the US reaps the returns. The Department of State helps attract the best students from around the world to American universities. Amid stagnating growth in the number of homegrown STEM PhD graduates, recruiting foreign students remains one of the strongest pathways for the US to expand its pool of technical talent, especially in strategic areas like batteries and semiconductors. Many of those students stay for years, if not the rest of their lives; even if they leave the country, they’ve already spent some of their most productive years in the US and will retain a wealth of professional connections with whom they’ll collaborate, thereby continuing to contribute to US science.

The State Department also establishes agreements between the US and other countries and helps broker partnerships between American and international universities. That helps scientists collaborate across borders on everything from global issues like climate change to research that requires equipment on opposite sides of the world, such as the measurement of gravitational waves.

The international development work of USAID in global health, poverty reduction, and conflict alleviation—now virtually shut down in its entirety—was designed to build up goodwill toward the US globally; it improved regional stability for decades. In addition to its inherent benefits, this allowed American scientists to safely access diverse geographies and populations, as well as plant and animal species not found in the US. Such international interchange played just as critical a role as government funding in many crucial inventions.

Several federal agencies, including the Centers for Disease Control and Prevention, the Environmental Protection Agency, and the National Oceanic and Atmospheric Administration, also help collect and aggregate critical data on disease, health trends, air quality, weather, and more from disparate sources that feed into the work of scientists across the country.

The National Institutes of Health, for example, has since 2015 been running the Precision Medicine Initiative, the only effort of its kind to collect extensive and granular health data from over 1 million Americans who volunteer their medical records, genetic history, and even Fitbit data to help researchers understand health disparities and develop personalized and more effective treatments for disorders from heart and lung disease to cancer. The data set, which is too expensive for any one university to assemble and maintain, has already been used in hundreds of papers that will lay the foundation for the next generation of life-saving pharmaceuticals.

Beyond fueling innovation, a well-supported science and technology ecosystem bolsters US national security and global influence. When people want to study at American universities, attend international conferences hosted on American soil, or move to the US to work or to found their own companies, the US stays the center of global innovation activity. This ensures that the country continues to get access to the best people and ideas, and gives it an outsize role in setting global scientific practices and priorities. US research norms, including academic freedom and a robust peer review system, become global research norms that lift the overall quality of science. International agencies like the World Health Organization take significant cues from American guidance.

US scientific leadership has long been one of the country’s purest tools of soft power and diplomacy as well. Countries keen to learn from the American innovation ecosystem and to have access to American researchers and universities have been more prone to partner with the US and align with its strategic priorities.

Just one example: Science diplomacy has long played an important role in maintaining the US’s strong relationship with the Netherlands, which is home to ASML, the only company in the world that can produce the extreme ultraviolet lithography machines needed to produce the most advanced semiconductors. These are critical for both AI development and national security.

International science cooperation has also served as a stabilizing force in otherwise difficult relationships. During the Cold War, the US and USSR continued to collaborate on the International Space Station; during the recent heightened economic competition between the US and China, the countries have remained each other’s top scientific partners. “Actively working together to solve problems that we both care about helps maintain the connections and the context but also helps build respect,” Seligsohn says.

The federal government itself is a significant beneficiary of the country’s convening power for technical expertise. Among other things, experts both inside and outside the government support its sound policymaking in science and technology. During the US Senate AI Insight Forums, co-organized by Senator Chuck Schumer through the fall of 2023, for example, the Senate heard from more than 150 experts, many of whom were born abroad and studying at American universities, working at or advising American companies, or living permanently in the US as naturalized American citizens.

Federal scientists and technical experts at government agencies also work on wide-ranging goals critical to the US, including building resilience in the face of an increasingly erratic climate; researching strategic technologies such as next-generation battery technology to reduce the country’s reliance on minerals not found in the US; and monitoring global infectious diseases to prevent the next pandemic.

“Every issue that the US faces, there are people that are trying to do research on it and there are partnerships that have to happen,” the State Department employee said.

A system in jeopardy

Now the breadth and velocity of the Trump administration’s actions has led to an unprecedented assault on every pillar upholding American scientific leadership.

For starters, the purging of tens of thousands—and perhaps soon hundreds of thousands—of federal workers is removing scientists and technologists from the government and paralyzing the ability of critical agencies to function. Across multiple agencies, science and technology fellowship programs, designed to bring in talented early-career staff with advanced STEM degrees, have shuttered. Many other federal scientists were among the thousands who were terminated as probationary employees, a status they held because of the way scientific roles are often contractually structured.

Some agencies that were supporting or conducting their own research, including the National Institutes of Health and the National Science Foundation, are no longer functionally operational. USAID has effectively shuttered, eliminating a bastion of US expertise, influence, and credibility overnight.

“Diplomacy is built on relationships. If we’ve closed all these clinics and gotten rid of technical experts in our knowledge base inside the government, why would any foreign government have respect for the US in our ability to hold our word and in our ability to actually be knowledgeable?” a terminated USAID worker said. “I really hope America can save itself.”

Now the Trump administration has sought to reverse some terminations after discovering that many were key to national security, including nuclear safety employees responsible for designing, building, and maintaining the country’s nuclear weapons arsenal. But many federal workers I spoke to can no longer imagine staying in the public sector. Some are considering going into industry. Others are wondering whether it will be better to move abroad.

“It’s just such a waste of American talent,” said Fiona Coleman, a terminated federal scientist, her voice cracking with emotion as she described the long years of schooling and training she and her colleagues went through to serve the government.

Many fear the US has also singlehandedly kneecapped its own ability to attract talent from abroad. Over the last 10 years, even as American universities have continued to lead the world, many universities in other countries have rapidly leveled up. That includes those in Canada, where liberal immigration policies and lower tuition fees have driven a 200% increase in international student enrollment over the last decade, according to Anna Esaki-Smith, cofounder of a higher-education research consultancy called Education Rethink and author of Make College Your Superpower.

Germany has also seen an influx, thanks to a growing number of English-taught programs and strong connections between universities and German industry. Chinese students, who once represented the largest share of foreign students in the US, are increasingly staying at home or opting to study in places like Hong Kong, Singapore, and the UK.

During the first Trump administration, many international students were already more reluctant to come to the US because of the president’s hostile rhetoric. With the return and rapid escalation of that rhetoric, Esaki-Smith is hearing from some universities that international students are declining their admissions offers.

Add to that the other recent developments—the potential dramatic cuts in federal research funding, the deletion of scores of rich public data sets on health and the environment, the clampdown on academic freedom for research that appears related to diversity, equity, and inclusion and the fear that these restrictions could ultimately encompass other politically charged topics like climate change or vaccines—and many more international science and engineering students could decide to head elsewhere.

“I’ve been hearing this increasingly from several postdocs and early-career professors, fearing the cuts in NIH or NSF grants, that they’re starting to look for funding or job opportunities in other countries,” Coleman told me. “And then we’re going to be training up the US’s competitors.”

The attacks could similarly weaken the productivity of those who stay at American universities. While many of the Trump administration’s actions are now being halted and scrutinized by US judges, the chaos has weakened a critical prerequisite for tackling the toughest research problems: a long-term stable environment. With reports that the NSF is combing through research grants for words like “women,” “diverse,” and “institutional” to determine whether they violate President Trump’s executive order on DEIA programs, a chilling effect is also setting in among federally funded academics uncertain whether they’ll get caught in the dragnet.

To scientists abroad, the situation in the US government has marked American institutions and researchers as potentially unreliable partners, several federal workers told me. If international researchers think collaborations with the US can end at any moment when funds are abruptly pulled or certain topics or keywords are suddenly blacklisted, many of them could steer clear and look to other countries. “I’m really concerned about the instability we’re showing,” another employee at the State Department said. “What’s the point in even engaging? Because science is a long-term initiative and process that outlasts administrations and political cycles.”

Meanwhile, international scientists have far more options these days for high-caliber colleagues to collaborate with outside America. In recent years, for example, China has made a remarkable ascent to become a global peer in scientific discoveries. By some metrics, it has even surpassed the US; it started accounting for more of the top 1% of most-cited papers globally, often called the Nobel Prize tier, back in 2019 and has continued to improve the quality of the rest of its research. 

Where Chinese universities can also entice international collaborators with substantial resources, the US is more limited in its ability to offer tangible funding, the State employee said. Until now, the US has maintained its advantage in part through the prestige of its institutions and its more open cultural norms, including stronger academic freedom. But several federal scientists warn that this advantage is dissipating. 

“America is made up of so many different people contributing to it. There’s such a powerful global community that makes this country what it is, especially in science and technology and academia and research. We’re going to lose that; there’s not a chance in the world that we’re not going to lose that through stuff like this,” says Brigid Cakouros, a federal scientist who was also terminated from USAID. “I have no doubt that the international science community will ultimately be okay. It’ll just be a shame for the US to isolate themselves from it.”

Doctors and patients are calling for more telehealth. Where is it?

Maggie Barnidge, 18, has been managing cystic fibrosis her whole life. But not long after she moved out of her home state to start college, she came down with pneumonia and went into liver failure. She desperately wanted to get in touch with her doctor back home, whom she’d been seeing since she was diagnosed as an infant and who knew which treatments worked best for her—but he wasn’t allowed to practice telemedicine across state lines. The local hospital, and doctors unfamiliar with her complicated medical history, would have to do. 

“A lot of what Maggie needed wasn’t a physical exam,” says Barnidge’s mother, Elizabeth. “It was a conversation: What tests should I be getting next? What did my labs look like? She just needed her doctor who knew her well.”  

But doctors are generally allowed to practice medicine only where they have a license. This means they cannot treat patients across state lines unless they also have a license in the patient’s state, and most physicians have one or two licenses at most. This has led to what Ateev Mehrotra, a physician and professor of health policy at the Brown University School of Public Health, calls an “inane” norm: A woman with a rare cancer boarding an airplane, at the risk of her chemotherapy-weakened immune system, to see a specialist thousands of miles away, for example, or a baby with a rare disease who’s repeatedly shuttled between Arizona and Massachusetts. 

While eligible physicians can currently apply to practice in states besides their own, this can be a burdensome and impractical process. For instance, let’s say you are an oncologist in Minnesota, and a patient from Kansas arrives at your office seeking treatment. The patient will probably want to do follow-up appointments via telehealth when possible, to avoid having to travel back to Minnesota. 

But if you are not yet licensed to practice in Kansas (and you probably are not), you can’t suddenly start practicing medicine there. You would first need to apply to do so, either through the Interstate Medical Licensure Compact (designed to streamline the process of obtaining a full license in another state, but at a price of $700 per year) or with Kansas’s board of medicine directly. Maybe this poses too great an administrative hurdle for you—you work long hours, and how will you find time to compile the necessary paperwork? Doctors can’t reasonably be expected to apply for licensure in all 50 states. The patient, then, either loses out on care or must shoulder the burden of traveling to Minnesota for a doctor’s visit. The only way to access telehealth, if that’s what the patient prefers, would be to cross into the state and log in—an option that might still be preferable to traveling all the way to the doctor’s office. These obstacles to care have led to a growing belief among health-care providers, policymakers, and patients that under certain circumstances, doctors should be able to treat their patients anywhere. 

Lately, telehealth has proved to be widely popular, too. The coronavirus emergency in 2020 served as proof of concept, demonstrating that new digital platforms for medicine were feasible—and often highly effective. One study showed that telehealth accounted for nearly a quarter of contacts between patients and providers during the first four months of the pandemic (up from 0.3% during the same period in 2019), and among Medicare users, nearly half had used telehealth in 2020—a 63-fold increase. This swift and dramatic shift came about because Congress and the Centers for Medicare and Medicaid Services had passed legislation to make more telehealth visits temporarily eligible for reimbursement (the payments a health-care provider receives from an insurance company for providing medical services), while state boards of medicine relaxed the licensing restrictions. Now, more providers were able to offer telehealth, and more patients were eager to receive medical care without leaving their homes.

Though in-person care remains standard, telehealth has gained a significant place in US medicine, increasing from 0.1% of total Medicare visits in 2019 to 5.3% in 2020 and 3.5% in 2021. By the end of 2023, more than one in 10 Medicare patients were still using telehealth. And in some specialties the rate is much higher: 37% of all mental-health visits in the third quarter of 2023 were telemedicine, as well as 10% of obstetric appointments, 10% of transplant appointments, and 11% of infectious-disease appointments. 

“Telehealth has broadened our ability to provide care in ways not imaginable prior to the pandemic,” says Tara Sklar, faculty director of the health law and policy program at the University of Arizona James E. Rogers College of Law. 

Traditionally, patients and providers alike have been skeptical that telehealth care can meet the standards of an in-person appointment. However, most people advocating for telehealth aren’t arguing that it should completely replace visiting your doctor, explains Carmel Shachar, director of Harvard Law School’s Health Law and Policy Clinic. Rather, “it’s a really useful way to improve access to care.” Digital medicine could help address a gap in care for seniors by eliminating the need for them to make an arduous journey to the doctor’s office; many older adults find they’re more likely to keep their follow-up appointments when they can do them remotely. Telemedicine could also help address the equity issues facing hourly employees, who might not be able to take a half or full day off work to attend an in-­person appointment. For them, the offer of a video call might make the difference between seeking and not seeking help. 

“It’s a modality that we’re not using to its fullest potential because we’re not updating our regulations to reflect the digital age,” Shachar says.

Last December, Congress extended most of the provisions increasing Medicare coverage for telehealth through the end of March 2025, including the assurances that patients can be in their homes when they receive care and that they don’t need to be in a rural area to be eligible for telemedicine. 

“We would love to have these flexibilities made permanent,” says Helen Hughes, medical director for the Johns Hopkins Office of Telemedicine. “It’s confusing to explain to our providers and patients the continued regulatory uncertainty and news articles implying that telehealth is at risk, only to have consistent extensions for the last five years. This uncertainty leads providers and patients to worry that this type of care is not permanent and probably stifles innovation and investment by health systems.” 

In the meantime, several strategies are being considered to facilitate telehealth across state lines. Some places—like Maryland, Virginia, and Washington, DC—offer “proximal reciprocity,” meaning that a physician licensed in any of those states can more efficiently be licensed in the others. And several states, like Arkansas and Idaho, say that out-of-state doctors can generally practice telemedicine within their borders as long as they are licensed in good standing in another state and are using the technology to provide follow-up care. Expanding on these ideas, some advocates say that an ideal approach might look similar to how we regulate driving across state lines: A driver’s license from one state generally permits you to drive anywhere in the country as long as you have a good record and obey the rules of the road in the state that you’re in. Another idea is to create a telemedicine-specific version of the Interstate Medical Licensure Compact (which deals only with full medical licenses) in which qualifying physicians can register to practice telehealth among all participating states via a centralized compact.

For the foreseeable future, telehealth policy in the US is locked in what Mehrotra calls “hand-to-hand warfare”—states duking it out within their own legislatures to try to determine rules and regulations for administering telemedicine. Meanwhile, advocates are also pushing for uniformity between states, as with the Uniform Law Commission’s Telehealth Act of 2022, which set out consistent terminology so that states can adopt similar telehealth laws. 

“We’ve always advanced our technologies, like what I can provide as a doctor—meds, tests, surgeries,” Mehrotra says. “But in 2024, the basic structure of how we deliver that care is very similar to 1964.” That is, we still ask people to come to a doctor’s office or emergency department for an in-person visit. 

“That’s what excites me about telehealth,” he says. “I think there’s the potential that we can deliver care in a better way.” 

Isabel Ruehl is a writer based in New York and an assistant editor at Harper’s Magazine.

Congress used to evaluate emerging technologies. Let’s do it again.

At about the time when personal computers charged into cubicle farms, another machine muscled its way into human resources departments and became a staple of routine employment screenings. By the early 1980s, some 2 million Americans annually found themselves strapped to a polygraph—a metal box that, in many people’s minds, detected deception. Most of those tested were not suspected crooks or spooks. 

Then the US Office of Technology Assessment, an independent office that had been created by Congress about a decade earlier to serve as its scientific consulting arm, got involved. The office reached out to Boston University researcher Leonard Saxe with an assignment: Evaluate polygraphs. Tell us the truth about these supposed truth-telling devices.

And so Saxe assembled a team of about a dozen researchers, including Michael Saks of Boston College, to begin a systematic review. The group conducted interviews, pored over existing studies, and embarked on new lines of research. A few months later, the OTA published a technical memo, “Scientific Validity of Polygraph Testing: A Research Review and Evaluation.” Despite the tests’ widespread use, the memo dutifully reported, “there is very little research or scientific evidence to establish polygraph test validity in screening situations, whether they be preemployment, preclearance, periodic or aperiodic, random, or ‘dragnet.’” These machines could not detect lies. 

Four years later, in 1987, critics at a congressional hearing invoked the OTA report as authoritative, comparing polygraphs derisively to “tea leaf reading or crystal ball gazing.” Congress soon passed strict limits on the use of polygraphs in the workplace. 

Over its 23-year history, the OTA would publish some 750 reports—lengthy, interdisciplinary assessments of specific technologies that proposed means of maximizing their benefits and minimizing harms. Their subjects included electronic surveillance, genetic engineering, hazardous-waste disposal, and remote sensing from outer space. Congress set its course: The office initiated studies only at the request of a committee chairperson, a ranking minority leader, or its 12-person bipartisan board. 

The investigations remained independent; staffers and consultants from both inside and outside government collaborated to answer timely and sometimes politicized questions. The reports addressed worries about alarming advances and tamped down scary-sounding hypotheticals. Some of those concerns no longer keep policymakers up at night. For instance, “Do Insects Transmit AIDS?” A 1987 OTA report correctly suggested that they don’t.

The office functioned like a debunking arm. It sussed out the snake oil. Lifted the lid on the Mechanical Turk. The reports saw through the alluring gleam of overhyped technologies. 

In the years since its unceremonious defunding, perennial calls have gone out: Rouse the office from the dead! And with advances in robotics, big data, and AI systems, these calls have taken on a new level of urgency. 

Like polygraphs, chatbots and search engines powered by so-called artificial intelligence come with a shimmer and a sheen of magical thinking. And if we’re not careful, politicians, employers, and other decision-makers may accept at face value the idea that machines can and should replace human judgment and discretion. 

A resurrected OTA might be the perfect body to rein in dangerous and dangerously overhyped technologies. “That’s what Congress needs right now,” says Ryan Calo at the University of Washington’s Tech Policy Lab and the Center for an Informed Public, “because otherwise Congress is going to, like, take Sam Altman’s word for everything, or Eric Schmidt’s.” (The CEO of OpenAI and the former CEO of Google have both testified before Congress.) Leaving it to tech executives to educate lawmakers is like having the fox tell you how to build your henhouse. Wasted resources and inadequate protections might be only the start. 

A man administers a lie detector test to a job
applicant in 1976. A 1983 report from the OTA debunked the efficacy of polygraphs.
LIBRARY OF CONGRESS

No doubt independent expertise still exists. Congress can turn to the Congressional Research Service, for example, or the National Academies of Sciences, Medicine, and Engineering. Other federal entities, such as the Office of Management and Budget and the Office of Science and Technology Policy, have advised the executive branch (and still existed as we went to press). “But they’re not even necessarily specialists,” Calo says, “and what they’re producing is very lightweight compared to what the OTA did. And so I really think we need OTA back.”  

What exists today, as one researcher puts it, is a “diffuse and inefficient” system. There is no central agency that wholly devotes itself to studying emerging technologies in a serious and dedicated way and advising the country’s 535 elected officials about potential impacts. The digestible summaries Congress receives from the Congressional Research Service provide insight but are no replacement for the exhaustive technical research and analytic capacity of a fully staffed and funded think tank. There’s simply nothing like the OTA, and no single entity replicates its incisive and instructive guidance. But there’s also nothing stopping Congress from reauthorizing its budget and bringing it back, except perhaps the lack of political will. 

“Congress Smiles, Scientists Wince”

The OTA had not exactly been an easy sell to the research community in 1972. At the time, it was only the third independent congressional agency ever established. As the journal Science put it in a headline that year, “The Office of Technology Assessment: Congress Smiles, Scientists Wince.” One researcher from Bell Labs told Science that he feared legislators would embark on “a clumsy, destructive attempt to manage national R&D,” but mostly the cringe seemed to stem from uncertainty about what exactly technology assessment entailed. 

The OTA’s first report, in 1974, examined bioequivalence, an essential part of evaluating generic drugs. Regulators were trying to figure out whether these drugs could be deemed comparable to their name-brand equivalents without lengthy and expensive clinical studies demonstrating their safety and efficacy. Unlike all the OTA’s subsequent assessments, this one listed specific policy recommendations, such as clarifying what data should be required in order to evaluatea generic drug and ensure uniformity and standardization in the regulatory approval process. The Food and Drug Administration later incorporated these recommendations into its own submission requirements. 

From then on, though, the OTA did not take sides. The office had not been set up to advise Congress on how to legislate. Rather, it dutifully followed through on its narrowly focused mandate: Do the research and provide policymakers with a well-reasoned set of options that represented a range of expert opinions.

Perhaps surprisingly, given the rise of commercially available PCs, in the first decade of its existence the OTA produced only a few reports on computing. One 1976 report touched on the automated control of trains. Others examined computerized x-ray imaging, better known as CT scans; computerized crime databases; and the use of computers in medical education. Over time, the office’s output steadily increased, eventually averaging 32 reports a year. Its budget swelled to $22 million; its staff peaked at 143. 

While it’s sometimes said that the future impact of a technology is beyond anyone’s imagination, several findings proved prescient. A 1982 report on electronic funds transfer, or EFT, predicted that financial transactions would increasingly be carried out electronically (an obvious challenge to paper currency and hard-copy checks). Another predicted that email, or what was then termed “electronic message systems,” would disrupt snail mail and the bottom line of the US Postal Service. 

In vetting the digital record-keeping that provides the basis for routine background checks, the office commissioned a study that produced a statistic still cited today, suggesting that only about a quarter of the records sent to the FBI were “complete, accurate, and unambiguous.” It was an indicator of a growing issue: computational systems that, despite seeming automated, are not free of human bias and error. 

Many of the OTA’s reports focus on specific events or technologies. One looked at Love Canal, the upstate New York neighborhood polluted by hazardous waste (a disaster, the report said, that had not yet been remediated by the Environmental Protection Agency’s Superfund cleanup program); another studied the Boston Elbow, a cybernetic limb (the verdict: decidedly mixed). The office examined the feasibility of a water pipeline connecting Alaska to California, the health effects of the Kuwait oil fires, and the news media’s use of satellite imagery. The office also took on issues we grapple with today—evaluating automatic record checks for people buying guns, scrutinizing the compensation for injuries allegedly caused by vaccines, and pondering whether we should explore Mars. 

The OTA made its biggest splash in 1984, when it published a background report criticizing the Strategic Defense Initiative (commonly known as “Star Wars”), a pet project of the Reagan administration that involved several exotic missile defense systems. Its lead author was the MIT physicist Ashton Carter, later secretary of defense in the second Obama administration. And the report concluded that a “perfect or near-perfect” system to defend against nuclear weapons was basically beyond the realm of the plausible; the possibility of deployment was “so remote that it should not serve as the basis of public expectation or national policy.” 

The report generated lots of clicks, so to speak, especially after the administration claimed that the OTA had divulged state secrets. These charges did not hold up and Star Wars never materialized, although there have been recent efforts to beef up the military’s offensive capacity in space. But for the work of an advisory body that did not play politics, the report made a big political hubbub. By some accounts, its subsequent assessments became so neutral that the office risked receding to the point of invisibility.

From a purely pragmatic point of view, the OTA wrote to be understood. A dozen reports from the early ’90s received “Blue Pencil Awards,” given by the National Association of Government Communicators for “superior government communication products and those who produce them.” None are copyrighted. All were freely reproduced and distributed, both in print and electronically. The entire archive is stored on CD-ROM, and digitized copies are still freely available for download on a website maintained by Princeton University, like an earnest oasis of competence in the cloistered world of federal documents. 

Assessments versus accountability

Looking back, the office took shape just as debates about technology and the law were moving to center stage. 

While the gravest of dangers may have changed in form and in scope, the central problem remains: Laws and lawmakers cannot keep up with rapid technological advances. Policymakers often face a choice between regulating with insufficient facts and doing nothing. 

In 2018, Adam Kinzinger, then a Republican congressman from Illinois, confessed to a panel on quantum computing: “I can understand about 50% of the things you say.” To some, his admission underscored a broader tech illiteracy afflicting those in power. But other commentators argued that members of Congress should not be expected to know it all—all the more reason to restaff an office like the OTA.

A motley chorus of voices have clamored for an OTA 2.0 over the years. One doctor wrote that the office could help address the “discordance between the amount of money spent and the actual level of health.” Tech fellows have said bringing it back could help Congress understand machine learning and AI. Hillary Clinton, as a Democratic presidential hopeful, floated the possibility of resurrecting the OTA in 2017. 

But Meg Leta Jones, a law scholar at Georgetown University, argues that assessing new technologies is the least of our problems. The kind of work the OTA did is now done by other agencies, such as the FTC, FCC, and National Telecommunications and Information Administration, she says: “The energy I would like to put into the administrative state is not on assessments, but it’s on actual accountability and enforcement.”

She sees the existing framework as built for the industrial age, not a digital one, and is among those calling for a more ambitious overhaul. There seems to be little political appetite for the creation of new agencies anyway. That said, Jones adds, “I wouldn’t be mad if they remade the OTA.” 

No one can know whether or how future administrations will address AI, Mars colonization, the safety of vaccines, or, for that matter, any other emerging technology that the OTA investigated in an earlier era. But if the new administration makes good on plans to deregulate many sectors, it’s worth noting some historic echoes. In 1995, when conservative politicians defunded the OTA, they did so in the name of efficiency. Critics of that move contend that the office probably saved the government money and argue that the purported cost savings associated with its elimination were largely symbolic. 

Jathan Sadowski, a research fellow at Monash University in Melbourne, Australia, who has written about the OTA’s history, says the conditions that led to its demise have only gotten more partisan, more politicized. This makes it difficult to envision a place for the agency today, he says—“There’s no room for the kind of technocratic naïveté that would see authoritative scientific advice cutting through the noise of politics.”

Congress purposely cut off its scientific advisory arm as part of a larger shake-up led by Newt Gingrich, then the House Speaker, whose pugilistic brand of populist conservatism promised “drain the swamp”–type reforms and launched what critics called a “war on science.” As a rationale for why the office was defunded, he said, “We constantly found scientists who thought what they were saying was not correct.” 

Once again, Congress smiled and scientists winced. Only this time it was because politicians had pulled the plug. 

Peter Andrey Smith, a freelance reporter, has contributed to Undark, the New Yorker, the New York Times Magazine, and WNYC’s Radiolab.

Inside the race to archive the US government’s websites

Over the past three weeks, the new US presidential administration has taken down thousands of government web pages related to public health, environmental justice, and scientific research. The mass takedowns stem from the new administration’s push to remove government information related to diversity and “gender ideology,” as well as scrutiny of various government agencies’ practices. 

USAID’s website is down. So are sites related to it, like childreninadversity.gov, as well as thousands of pages from the Census Bureau, the Centers for Disease Control and Prevention, and the Office of Justice Programs.

“We’ve never seen anything like this,” says David Kaye, professor of law at the University of California, Irvine, and the former UN Special Rapporteur for freedom of opinion and expression. “I don’t think any of us know exactly what is happening. What we can see is government websites coming down, databases of essential public interest. The entirety of the USAID website.”

But as government web pages go dark, a collection of organizations are trying to archive as much data and information as possible before it’s gone for good. The hope is to keep a record of what has been lost for scientists and historians to be able to use in the future.

Data archiving is generally considered to be nonpartisan, but the recent actions of the administration have spurred some in the preservation community to stand up. 

“I consider the actions of the current administration an assault on the entire scientific enterprise,” says Margaret Hedstrom, professor emerita of information at the University of Michigan.

Various organizations are trying to scrounge up as much data as possible. One of the largest projects is the End of Term Web Archive, a nonpartisan coalition of many organizations that aims to make a copy of all government data at the end of each presidential term. The EoT Archive allows individuals to nominate specific websites or data sets for preservation.

“All we can do is collect what has been published and archive it and make sure it’s publicly accessible for the future,” says James Jacobs, US government information librarian at Stanford University, who is one of the people running the EoT Archive. 

Other organizations are taking a specific angle on data collection. For example, the Open Environmental Data Project (OEDP) is trying to capture data related to climate science and environmental justice. “We’re trying to track what’s getting taken down,” says Katie Hoeberling, director of policy initiatives at OEDP. “I can’t say with certainty exactly how much of what used to be up is still up, but we’re seeing, especially in the last couple weeks, an accelerating rate of data getting taken down.” 

In addition to tracking what’s happening, OEDP is actively backing up relevant data. It actually began this process in November, to capture the data at the end of former president Biden’s term. But efforts have ramped up in the last couple weeks. “Things were a lot calmer prior to the inauguration,” says Cathy Richards, a technologist at OEDP. “It was the second day of the new administration that the first platform went down. At that moment, everyone realized, ‘Oh, no—we have to keep doing this, and we have to keep working our way down this list of data sets.’”

This kind of work is crucial because the US government holds invaluable international and national data relating to climate. “These are irreplaceable repositories of important climate information,” says Lauren Kurtz, executive director of the Climate Science Legal Defense Fund. “So fiddling with them or deleting them means the irreplaceable loss of critical information. It’s really quite tragic.”

Like the OEDP, the Catalyst Cooperative is trying to make sure data related to climate and energy is stored and accessible for researchers. Both are part of the Public Environmental Data Partners, a collective of organizations dedicated to preserving federal environmental data. ”We have tried to identify data sets that we know our communities make use of to make decisions about what electricity we should procure or to make decisions about resiliency in our infrastructure planning,” says Christina Gosnell, cofounder and president of Catalyst. 

Archiving can be a difficult task; there is no one easy way to store all the US government’s data. “Various federal agencies and departments handle data preservation and archiving in a myriad of ways,” says Gosnell. There’s also no one who has a complete list of all the government websites in existence. 

This hodgepodge of data means that in addition to using web crawlers, which are tools used to capture snapshots of websites and data, archivists often have to manually scrape data as well. Additionally, sometimes a data set will be behind a login address or captcha to prevent scraper tools from pulling the data. Web scrapers also sometimes miss key features on a site. For example, sites will often have plenty of links to other pieces of information that aren’t captured in a scrape. Or the scrape may just not work because of something to do with a website’s structure. Therefore, having a person in the loop double-checking the scraper’s work or capturing data manually is often the only way to ensure that the information is properly collected.

And there are questions about whether scraping the data will really be enough. Restoring websites and complex data sets is often not a simple process. “It becomes extraordinarily difficult and costly to attempt to rescue and salvage the data,” says Hedstrom. “It is like draining a body of blood and expecting the body to continue to function. The repairs and attempts to recover are sometimes insurmountable where we need continuous readings of data.”

“All of this data archiving work is a temporary Band-Aid,” says Gosnell. “If data sets are removed and are no longer updated, our archived data will become increasingly stale and thus ineffective at informing decisions over time.” 

These effects may be long-lasting. “You won’t see the impact of that until 10 years from now, when you notice that there’s a gap of four years of data,” says Jacobs. 

Many digital archivists stress the importance of understanding our past. “We can all think about our own family photos that have been passed down to us and how important those different documents are,” says Trevor Owens, chief research officer at the American Institute of Physics and former director of digital services at the Library of Congress. “That chain of connection to the past is really important.”

“It’s our library; it’s our history,” says Richards. “This data is funded by taxpayers, so we definitely don’t want all that knowledge to be lost when we can keep it, store it, potentially do something with it and continue to learn from it.”

Three reasons Meta will struggle with community fact-checking

Earlier this month, Mark Zuckerberg announced that Meta will cut back on its content moderation efforts and eliminate fact-checking in the US in favor of the more “democratic” approach that X (formerly Twitter) calls Community Notes, rolling back protections that he claimed had been developed only in response to media and government pressure.

The move is raising alarm bells, and rightly so. Meta has left a trail of moderation controversies in its wake, from overmoderating images of breastfeeding women to undermoderating hate speech in Myanmar, contributing to the genocide of Rohingya Muslims. Meanwhile, ending professional fact-checking creates the potential for misinformation and hate to spread unchecked.

Enlisting volunteers is how moderation started on the Internet, long before social media giants realized that centralized efforts were necessary. And volunteer moderation can be successful, allowing for the development of bespoke regulations aligned with the needs of particular communities. But without significant commitment and oversight from Meta, such a system cannot contend with how much content is shared across the company’s platforms, and how fast. In fact, the jury is still out on how well it works at X, which is used by 21% of Americans (Meta’s are significantly more popular—Facebook alone is used by 70% of Americans, according to Pew).  

Community Notes, which started in 2021 as Birdwatch, is a community-driven moderation system on X that allows users who sign up for the program to add context to posts. Having regular users provide public fact-checking is relatively new, and so far results are mixed. For example, researchers have found that participants are more likely to challenge content they disagree with politically and that flagging content as false does not reduce engagement, but they have also found that the notes are typically accurate and can help reduce the spread of misleading posts

I’m a community moderator who researches community moderation. Here’s what I’ve learned about the limitations of relying on volunteers for moderation—and what Meta needs to do to succeed: 

1. The system will miss falsehoods and could amplify hateful content

There is a real risk under this style of moderation that only posts about things that a lot of people know about will get flagged in a timely manner—or at all. Consider how a post with a picture of a death cap mushroom and the caption “Tasty” might be handled under Community Notes–style moderation. If an expert in mycology doesn’t see the post, or sees it only after it’s been widely shared, it may not get flagged as “Poisonous, do not eat”—at least not until it’s too late. Topic areas that are more esoteric will be undermoderated. This could have serious impacts on both individuals (who may eat a poisonous mushroom) and society (if a falsehood spreads widely). 

Crucially, X’s Community Notes aren’t visible to readers when they are first added. A note becomes visible to the wider user base only when enough contributors agree that it is accurate by voting for it. And not all votes count. If a note is rated only by people who tend to agree with each other, it won’t show up. X does not make a note visible until there’s agreement from people who have disagreed on previous ratings. This is an attempt to reduce bias, but it’s not foolproof. It still relies on people’s opinions about a note and not on actual facts. Often what’s needed is expertise.

I moderate a community on Reddit called r/AskHistorians. It’s a public history site with over 2 million members and is very strictly moderated. We see people get facts wrong all the time. Sometimes these are straightforward errors. But sometimes there is hateful content that takes experts to recognize. One time a question containing a Holocaust-denial dog whistle escaped review for hours and ended up amassing hundreds of upvotes before it was caught by an expert on our team. Hundreds of people—probably with very different voting patterns and very different opinions on a lot of topics—not only missed the problematic nature of the content but chose to promote it through upvotes. This happens with answers to questions, too. People who aren’t experts in history will upvote outdated, truthy-sounding answers that aren’t actually correct. Conversely, they will downvote good answers if they reflect viewpoints that are tough to swallow. 

r/AskHistorians works because most of its moderators are expert historians. If Meta wants its Community Notes–style program to work, it should  make sure that the people with the knowledge to make assessments see the posts and that expertise is accounted for in voting, especially when there’s a misalignment between common understanding and expert knowledge. 

2. It won’t work without well-supported volunteers  

Meta’s paid content moderators review the worst of the worst—including gore, sexual abuse and exploitation, and violence. As a result, many have suffered severe trauma, leading to lawsuits and unionization efforts. When Meta cuts resources from its centralized moderation efforts, it will be increasingly up to unpaid volunteers to keep the platform safe. 

Community moderators don’t have an easy job. On top of exposure to horrific content, as identifiable members of their communities, they are also often subject to harassment and abuse—something we experience daily on r/AskHistorians. However, community moderators moderate only what they can handle. For example, while I routinely manage hate speech and violent language, as a moderator of a text-based community I am rarely exposed to violent imagery. Community moderators also work as a team. If I do get exposed to something I find upsetting or if someone is being abusive, my colleagues take over and provide emotional support. I also care deeply about the community I moderate. Care for community, supportive colleagues, and self-selection all help keep volunteer moderators’ morale high(ish). 

It’s unclear how Meta’s new moderation system will be structured. If volunteers choose what content they flag, will that replicate X’s problem, where partisanship affects which posts are flagged and how? It’s also unclear what kind of support the platform will provide. If volunteers are exposed to content they find upsetting, will Meta—the company that is currently being sued for damaging the mental health of its paid content moderators—provide social and psychological aid? To be successful, the company will need to ensure that volunteers have access to such resources and are able to choose the type of content they moderate (while also ensuring that this self-selection doesn’t unduly influence the notes).    

3. It can’t work without protections and guardrails 

Online communities can thrive when they are run by people who deeply care about them. However, volunteers can’t do it all on their own. Moderation isn’t just about making decisions on what’s “true” or “false.” It’s also about identifying and responding to other kinds of harmful content. Zuckerberg’s decision is coupled with other changes to its community standards that weaken rules around hateful content in particular. Community moderation is part of a broader ecosystem, and it becomes significantly harder to do it when that ecosystem gets poisoned by toxic content. 

I started moderating r/AskHistorians in 2020 as part of a research project to learn more about the behind-the-scenes experiences of volunteer moderators. While Reddit had started addressing some of the most extreme hate on its platform by occasionally banning entire communities, many communities promoting misogyny, racism, and all other forms of bigotry were permitted to thrive and grow. As a result, my early field notes are filled with examples of extreme hate speech, as well as harassment and abuse directed at moderators. It was hard to keep up with. 

But halfway through 2020, something happened. After a milquetoast statement about racism from CEO Steve Huffman, moderators on the site shut down their communities in protest. And to its credit, the platform listened. Reddit updated its community standards to explicitly prohibit hate speech and began to enforce the policy more actively. While hate is still an issue on Reddit, I see far less now than I did in 2020 and 2021. Community moderation needs robust support because volunteers can’t do it all on their own. It’s only one tool in the box. 

If Meta wants to ensure that its users are safe from scams, exploitation, and manipulation in addition to hate, it cannot rely solely on community fact-checking. But keeping the user base safe isn’t what this decision aims to do. It’s a political move to curry favor with the new administration. Meta could create the perfect community fact-checking program, but because this decision is coupled with weakening its wider moderation practices, things are going to get worse for its users rather than better. 

Sarah Gilbert is research director for the Citizens and Technology Lab at Cornell University.

There can be no winners in a US-China AI arms race

The United States and China are entangled in what many have dubbed an “AI arms race.” 

In the early days of this standoff, US policymakers drove an agenda centered on “winning” the race, mostly from an economic perspective. In recent months, leading AI labs such as OpenAI and Anthropic got involved in pushing the narrative of “beating China” in what appeared to be an attempt to align themselves with the incoming Trump administration. The belief that the US can win in such a race was based mostly on the early advantage it had over China in advanced GPU compute resources and the effectiveness of AI’s scaling laws.

But now it appears that access to large quantities of advanced compute resources is no longer the defining or sustainable advantage many had thought it would be. In fact, the capability gap between leading US and Chinese models has essentially disappeared, and in one important way the Chinese models may now have an advantage: They are able to achieve near equivalent results while using only a small fraction of the compute resources available to the leading Western labs.    

The AI competition is increasingly being framed within narrow national security terms, as a zero-sum game, and influenced by assumptions that a future war between the US and China, centered on Taiwan, is inevitable. The US has employed “chokepoint” tactics to limit China’s access to key technologies like advanced semiconductors, and China has responded by accelerating its efforts toward self-sufficiency and indigenous innovation, which is causing US efforts to backfire.

Recently even outgoing US Secretary of Commerce Gina Raimondo, a staunch advocate for strict export controls, finally admitted that using such controls to hold back China’s progress on AI and advanced semiconductors is a “fool’s errand.” Ironically, the unprecedented export control packages targeting China’s semiconductor and AI sectors have unfolded alongside tentative bilateral and multilateral engagements to establish AI safety standards and governance frameworks—highlighting a paradoxical desire of both sides to compete and cooperate. 

When we consider this dynamic more deeply, it becomes clear that the real existential threat ahead is not from China, but from the weaponization of advanced AI by bad actors and rogue groups who seek to create broad harms, gain wealth, or destabilize society. As with nuclear arms, China, as a nation-state, must be careful about using AI-powered capabilities against US interests, but bad actors, including extremist organizations, would be much more likely to abuse AI capabilities with little hesitation. Given the asymmetric nature of AI technology, which is much like cyberweapons, it is very difficult to fully prevent and defend against a determined foe who has mastered its use and intends to deploy it for nefarious ends. 

Given the ramifications, it is incumbent on the US and China as global leaders in developing AI technology to jointly identify and mitigate such threats, collaborate on solutions, and cooperate on developing a global framework for regulating the most advanced models—instead of erecting new fences, small or large, around AI technologies and pursing policies that deflect focus from the real threat.

It is now clearer than ever that despite the high stakes and escalating rhetoric, there will not and cannot be any long-term winners if the intense competition continues on its current path. Instead, the consequences could be severe—undermining global stability, stalling scientific progress, and leading both nations toward a dangerous technological brinkmanship. This is particularly salient given the importance of Taiwan and the global foundry leader TSMC in the AI stack, and the increasing tensions around the high-tech island. 

Heading blindly down this path will bring the risk of isolation and polarization, threatening not only international peace but also the vast potential benefits AI promises for humanity as a whole.

Historical narratives, geopolitical forces, and economic competition have all contributed to the current state of the US-China AI rivalry. A recent report from the US-China Economic and Security Review Commission, for example, frames the entire issue in binary terms, focused on dominance or subservience. This “winner takes all” logic overlooks the potential for global collaboration and could even provoke a self-fulfilling prophecy by escalating conflict. Under the new Trump administration this dynamic will likely become more accentuated, with increasing discussion of a Manhattan Project for AI and redirection of US military resources from Ukraine toward China

Fortunately, a glimmer of hope for a responsible approach to AI collaboration is appearing now as Donald Trump recently  posted on January 17 that he’d restarted direct dialogue with Chairman Xi Jinping regarding various areas of collaboration, and given past cooperation should continue to be “partners and friends.” The outcome of the TikTok drama, putting Trump at odds with sharp China critics in his own administration and Congress, will be a preview of how his efforts to put US China relations on a less confrontational trajectory.

The promise of AI for good

Western mass media usually focuses on attention-grabbing issues described in terms like the “existential risks of evil AI.” Unfortunately, the AI safety experts who get the most coverage often recite the same narratives, scaring the public. In reality, no credible research shows that more capable AI will become increasingly evil. We need to challenge the current false dichotomy of pure accelerationism versus doomerism to allow for a model more like collaborative acceleration

It is important to note the significant difference between the way AI is perceived in Western developed countries and developing countries. In developed countries the public sentiment toward AI is 60% to 70% negative, while in the developing markets the positive ratings are 60% to 80%. People in the latter places have seen technology transform their lives for the better in the past decades and are hopeful AI will help solve the remaining issues they face by improving education, health care, and productivity, thereby elevating their quality of life and giving them greater world standing. What Western populations often fail to realize is that those same benefits could directly improve their lives as well, given the high levels of inequity even in developed markets. Consider what progress would be possible if we reallocated the trillions that go into defense budgets each year to infrastructure, education, and health-care projects. 

Once we get to the next phase, AI will help us accelerate scientific discovery, develop new drugs, extend our health span, reduce our work obligations, and ensure access to high-quality education for all. This may sound idealistic, but given current trends, most of this can become a reality within a generation, and maybe sooner. To get there we’ll need more advanced AI systems, which will be a much more challenging goal if we divide up compute/data resources and research talent pools. Almost half of all top AI researchers globally (47%) were born or educated in China, according to industry studies. It’s hard to imagine how we could have gotten where we are without the efforts of Chinese researchers. Active collaboration with China on joint AI research could be pivotal to supercharging progress with a major infusion of quality training data and researchers. 

The escalating AI competition between the US and China poses significant threats to both nations and to the entire world. The risks inherent in this rivalry are not hypothetical—they could lead to outcomes that threaten global peace, economic stability, and technological progress. Framing the development of artificial intelligence as a zero-sum race undermines opportunities for collective advancement and security. Rather than succumb to the rhetoric of confrontation, it is imperative that the US and China, along with their allies, shift toward collaboration and shared governance.

Our recommendations for policymakers:

  1. Reduce national security dominance over AI policy. Both the US and China must recalibrate their approach to AI development, moving away from viewing AI primarily as a military asset. This means reducing the emphasis on national security concerns that currently dominate every aspect of AI policy. Instead, policymakers should focus on civilian applications of AI that can directly benefit their populations and address global challenges, such as health care, education, and climate change. The US also needs to investigate how to implement a possible universal basic income program as job displacement from AI adoption becomes a bigger issue domestically. 
    • 2. Promote bilateral and multilateral AI governance. Establishing a robust dialogue between the US, China, and other international stakeholders is crucial for the development of common AI governance standards. This includes agreeing on ethical norms, safety measures, and transparency guidelines for advanced AI technologies. A cooperative framework would help ensure that AI development is conducted responsibly and inclusively, minimizing risks while maximizing benefits for all.
    • 3. Expand investment in detection and mitigation of AI misuse. The risk of AI misuse by bad actors, whether through misinformation campaigns, telecom, power, or financial system attacks, or cybersecurity attacks with the potential to destabilize society, is the biggest existential threat to the world today. Dramatically increasing funding for and international cooperation in detecting and mitigating these risks is vital. The US and China must agree on shared standards for the responsible use of AI and collaborate on tools that can monitor and counteract misuse globally.
    • 4. Create incentives for collaborative AI research. Governments should provide incentives for academic and industry collaborations across borders. By creating joint funding programs and research initiatives, the US and China can foster an environment where the best minds from both nations contribute to breakthroughs in AI that serve humanity as a whole. This collaboration would help pool talent, data, and compute resources, overcoming barriers that neither country could tackle alone. A global effort akin to the CERN for AI will bring much more value to the world, and a peaceful end, than a Manhattan Project for AI, which is being promoted by many in Washington today. 
    • 5. Establish trust-building measures. Both countries need to prevent misinterpretations of AI-related actions as aggressive or threatening. They could do this via data-sharing agreements, joint projects in nonmilitary AI, and exchanges between AI researchers. Reducing import restrictions for civilian AI use cases, for example, could help the nations rebuild some trust and make it possible for them to discuss deeper cooperation on joint research. These measures would help build transparency, reduce the risk of miscommunication, and pave the way for a less adversarial relationship.
    • 6. Support the development of a global AI safety coalition. A coalition that includes major AI developers from multiple countries could serve as a neutral platform for addressing ethical and safety concerns. This coalition would bring together leading AI researchers, ethicists, and policymakers to ensure that AI progresses in a way that is safe, fair, and beneficial to all. This effort should not exclude China, as it remains an essential partner in developing and maintaining a safe AI ecosystem.
    • 7. Shift the focus toward AI for global challenges. It is crucial that the world’s two AI superpowers use their capabilities to tackle global issues, such as climate change, disease, and poverty. By demonstrating the positive societal impacts of AI through tangible projects and presenting it not as a threat but as a powerful tool for good, the US and China can reshape public perception of AI. 

    Our choice is stark but simple: We can proceed down a path of confrontation that will almost certainly lead to mutual harm, or we can pivot toward collaboration, which offers the potential for a prosperous and stable future for all. Artificial intelligence holds the promise to solve some of the greatest challenges facing humanity, but realizing this potential depends on whether we choose to race against each other or work together. 

    The opportunity to harness AI for the common good is a chance the world cannot afford to miss.


    Alvin Wang Graylin

    Alvin Wang Graylin is a technology executive, author, investor, and pioneer with over 30 years of experience shaping innovation in AI, XR (extended reality), cybersecurity, and semiconductors. Currently serving as global vice president at HTC, Graylin was the company’s China president from 2016 to 2023. He is the author of Our Next Reality.

    Paul Triolo

    Paul Triolo is a partner for China and technology policy lead at DGA-Albright Stonebridge Group. He advises clients in technology, financial services, and other sectors as they navigate complex political and regulatory matters in the US, China, the European Union, India, and around the world.

    We need to protect the protocol that runs Bluesky

    Last week, when Mark Zuckerberg announced that Meta would be ending third-party fact-checking, it was a shocking pivot, but not exactly surprising. It’s just the latest example of a billionaire flip-flop affecting our social lives on the internet. 

    After January 6, 2021, Zuckerberg bragged to Congress about Facebook’s “industry-leading fact-checking program” and banned Donald Trump from the platform. But just two years later, he welcomed Trump back. And last year Zuckerberg was privately reassuring the conservative congressman Jim Jordan that Meta will no longer demote questionable content while it’s being fact-checked. 

    Now, not only is Meta ending fact-checking completely; it is loosening rules around hate speech, allowing horrendous personal attacks on migrants and trans people, for example, on its platforms. 

    And Zuckerberg isn’t the only social media CEO careening all over the road: Elon Musk, since buying Twitter in 2022 and touting free speech as “the bedrock of a functioning democracy,” has suspended journalists, restored tens of thousands of banned users (including white nationalists), brought back political advertising, and weakened verification and harassment policies. 

    Unfortunately, these capricious billionaires can do whatever they want because of an ownership model that privileges singular, centralized control in exchange for shareholder returns.

    And this has led to a constantly shifting digital environment in which people can lose their communication pathways and livelihoods in a second, with no recourse, as opaque rules change. 

    The internet doesn’t need to be like this. As luck would have it, a new way is emerging just in time. 

    If you’ve heard of Bluesky, you’ve probably heard of it as a clone of Twitter where liberals can take refuge. But under the hood it’s structured fundamentally differently—in a way that could point us to a healthier internet for everyone, regardless of politics or identity. 

    Just like email, Bluesky sits on top of an open protocol, in this case known as the AT Protocol. In practice, that means that anyone can build on it. Just as you wouldn’t need anyone’s permission to start a newsletter company built on email, people are starting to share remixed versions of their social media feeds, built on Bluesky. This sounds like a small thing, but think about all the harms enabled by social media companies’ algorithms in the last decade: insurrection, radicalization, self-harm, bullying. Bluesky enables users to collaborate on verification and moderation by sharing block lists and labels. Letting people shape their own experience of social media is nothing short of revolutionary. 

    And importantly, if you decide that you don’t agree with Bluesky’s design and moderation decisions, you can build something else on the same infrastructure and use that instead. This is fundamentally different from the dominant, centralized social media that has prevailed until now.

    At the core of Bluesky’s philosophy is the idea that instead of being centralized in the hands of one person or institution, social media governance should obey the principle of subsidiarity. The Nobel Prize–winning economist Elinor Ostrom found, through studying grassroots solutions to local environmental problems around the world, that some problems are best solved locally, while others are best solved at a higher level. 

    In terms of content moderation, posts related to child sexual abuse or terrorism are best handled by professionals trained to help keep millions or billions safe. But a lot of decisions about speech can be solved in each community, or even user by user as people assemble Bluesky block lists. 

    So all the right elements are currently in place at Bluesky to usher in this new architecture for social media: independent ownership, newfound popularity, a stark contrast with other dominant platforms, and right-minded leadership. But challenges remain, and we can’t count on Bluesky to do this right without support. 

    Critics have pointed out that Bluesky has yet to turn a profit and is currently running on venture capital, the same corporate structure that brought us Facebook, Twitter, and other social media companies. As of now, there’s no option to exit Bluesky and take your data and network with you, because there are no other servers that run the AT Protocol. Bluesky CEO Jay Graber deserves credit for her stewardship so far, and for attempting to avoid the dangers of advertising incentives. But the process by which capitalism degrades tech products is so predictable that Cory Doctorow coined a now-popular term for it: enshittification.

    That’s why we need to act now to secure the foundation of this digital future and make it enshittification-proof. This week, prominent technologists started a new project, which we at New_ Public are supporting, called Free Our Feeds. There are three parts: First, Free Our Feeds wants to create a nonprofit foundation to govern and protect the AT Protocol, outside of Bluesky the company. We also need to build redundant servers so all users can leave with their data or build anything they want—regardless of policies set by Bluesky. Finally, we need to spur the development of a whole ecosystem built on this tech with seed money and expertise. 

    It’s worth noting that this is not a hostile takeover: Bluesky and Graber recognize the importance of this effort and have signaled their approval. But the point is, it can’t rely on them. To free us from fickle billionaires, some of the power has to reside outside Bluesky, Inc. 

    If we get this right, so much is possible. Not too long ago, the internet was full of builders and people working together: the open web. Email. Podcasts. Wikipedia is one of the best examples—a collaborative project to create one of the web’s best free, public resources. And the reason we still have it today is the infrastructure built up around it: The nonprofit Wikimedia Foundation protects the project and insulates it from the pressures of capitalism. When’s the last time we collectively built anything as good?

    We can shift the balance of power and reclaim our social lives from these companies and their billionaires. This is an opportunity to bring much more independence, innovation, and local control to our online conversations. We can finally build the “Wikipedia of social media,” or whatever we want. But we need to act, because the future of the internet can’t depend on whether one of the richest men on Earth wakes up on the wrong side of the bed. 

    Eli Pariser is author of The Filter Bubble and Co-Director of New_ Public, a nonprofit R&D lab that’s working to reimagine social media. 

    Deepti Doshi is a Co-Director of New_ Public and was a director at Meta.

    A New York legislator wants to pick up the pieces of the dead California AI bill

    The first Democrat in New York history with a computer science background wants to revive some of the ideas behind the failed California AI safety bill, SB 1047, with a new version in his state that would regulate the most advanced AI models. It’s called the RAISE Act, an acronym for “Responsible AI Safety and Education.”

    Assemblymember Alex Bores hopes his bill, currently an unpublished draft—subject to change—that MIT Technology Review has seen, will address many of the concerns that blocked SB 1047 from passing into law.

    SB 1047 was, at first, thought to be a fairly modest bill that would pass without much fanfare. In fact, it flew through the California statehouse with huge margins and received significant public support.

    However, before it even landed on Governor Gavin Newsom’s desk for signature in September, it sparked an intense national fight. Google, Meta, and OpenAI came out against the bill, alongside top congressional Democrats like Nancy Pelosi and Zoe Lofgren. Even Hollywood celebrities got involved, with Jane Fonda and Mark Hamill expressing support for the bill. 

    Ultimately, Newsom vetoed SB 1047, effectively killing regulation of so-called frontier AI models not just in California but, with the lack of laws on the national level, anywhere in the US, where the most powerful systems are developed.

    Now Bores hopes to revive the battle. The main provisions in the RAISE Act include requiring AI companies to develop safety plans for the development and deployment of their models. 

    The bill also provides protections for whistleblowers at AI companies. It forbids retaliation against an employee who shares information about an AI model in the belief that it may cause “critical harm”; such whistleblowers can report the information to the New York attorney general. One way the bill defines critical harm is the use of an AI model to create a chemical, biological, radiological, or nuclear weapon that results in the death or serious injury of 100 or more people. 

    Alternatively, a critical harm could be a use of the AI model that results in 100 or more deaths or at least $1 billion in damages in an act with limited human oversight that if committed by a human would constitute a crime requiring intent, recklessness, or gross negligence.

    The safety plans would ensure that a company has cybersecurity protections in place to prevent unauthorized access to a model. The plan would also require testing of models to assess risks before and after training, as well as detailed descriptions of procedures to assess the risks associated with post-training modifications. For example, some current AI systems have safeguards that can be easily and cheaply removed by a malicious actor. A safety plan would have to address how the company plans to mitigate these actions.

    The safety plans would then be audited by a third party, like a nonprofit with technical expertise that currently tests AI models. And if violations are found, the bill empowers the attorney general of New York to issue fines and, if necessary, go to the courts to determine whether to halt unsafe development. 

    A different flavour of bill

    The safety plans and external audits were elements of SB 1047, but Bores aims to differentiate his bill from the California one. “We focused a lot on what the feedback was for 1047,” he says. “Parts of the criticism were in good faith and could make improvements. And so we’ve made a lot of changes.” 

    The RAISE Act diverges from SB 1047 in a few ways. For one, SB 1047 would have created the Board of Frontier Models, tasked with approving updates to the definitions and regulations around these AI models, but the proposed act would not create a new government body. The New York bill also doesn’t create a public cloud computing cluster, which SB 1047 would have done. The cluster was intended to support projects to develop AI for the public good. 

    The RAISE Act doesn’t have SB 1047’s requirement that companies be able to halt all operations of their model, a capability sometimes referred to as a “kill switch.” Some critics alleged that the shutdown provision of SB 1047 would harm open-source models, since developers can’t shut down a model someone else may now possess (even though SB 1047 had an exemption for open-source models).

    The RAISE Act avoids the fight entirely. SB 1047 referred to an “advanced persistent threat” associated with bad actors trying to steal information during model training. The RAISE Act does away with that definition, sticking to addressing critical harms from covered models.

    Focusing on the wrong issues?

    Bores’ bill is very specific with its definitions in an effort to clearly delineate what this bill is and isn’t about. The RAISE Act doesn’t address some of the current risks from AI models, like bias, discrimination, and job displacement. Like SB 1047, it is very focused on catastrophic risks from frontier AI models. 

    Some in the AI community believe this focus is misguided. “We’re broadly supportive of any efforts to hold large models accountable,” says Kate Brennan, associate director of the AI Now Institute, which conducts AI policy research.

    “But defining critical harms only in terms of the most catastrophic harms from the most advanced models overlooks the material risks that AI poses, whether it’s workers subject to surveillance mechanisms, prone to workplace injuries because of algorithmically managed speed rates, climate impacts of large-scale AI systems, data centers exerting massive pressure on local power grids, or data center construction sidestepping key environmental protections,” she says.

    Bores has worked on other bills addressing current harms posed by AI systems, like discrimination and lack of transparency. That said, Bores is clear that this new bill is aimed at mitigating catastrophic risks from more advanced models. “We’re not talking about any model that exists right now,” he says. “We are talking about truly frontier models, those on the edge of what we can build and what we understand, and there is risk in that.” 

    The bill would cover only models that pass a certain threshold for how many computations their training required, typically measured in FLOPs (floating-point operations). In the bill, a covered model is one that requires more than 1026 FLOPs in its training and costs over $100 million. For reference, GPT-4 is estimated to have required 1025 FLOPs. 

    This approach may draw scrutiny from industry forces. “While we can’t comment specifically on legislation that isn’t public yet, we believe effective regulation should focus on specific applications rather than broad model categories,” says a spokesperson at Hugging Face, a company that opposed SB 1047.

    Early days

    The bill is in its nascent stages, so it’s subject to many edits in the future, and no opposition has yet formed. There may already be lessons to be learned from the battle over SB 1047, however. “There’s significant disagreement in the space, but I think debate around future legislation would benefit from more clarity around the severity, the likelihood, and the imminence of harms,” says Scott Kohler, a scholar at the Carnegie Endowment for International Peace, who tracked the development of SB 1047. 

    When asked about the idea of mandated safety plans for AI companies, assemblymember Edward Ra, a Republican who hasn’t yet seen a draft of the new bill yet, said: “I don’t have any general problem with the idea of doing that. We expect businesses to be good corporate citizens, but sometimes you do have to put some of that into writing.” 

    Ra and Bores co chair the New York Future Caucus, which aims to bring together lawmakers 45 and under to tackle pressing issues that affect future generations.

    Scott Wiener, a California state senator who sponsored SB 1047, is happy to see that his initial bill, even though it failed, is inspiring further legislation and discourse. “The bill triggered a conversation about whether we should just trust the AI labs to make good decisions, which some will, but we know from past experience, some won’t make good decisions, and that’s why a level of basic regulation for incredibly powerful technology is important,” he says.

    He has his own plans to reignite the fight: “We’re not done in California. There will be continued work in California, including for next year. I’m optimistic that California is gonna be able to get some good things done.”

    And some believe the RAISE Act will highlight a notable contradiction: Many of the industry’s players insist that they want regulation, but when any regulation is proposed, they fight against it. “SB 1047 became a referendum on whether AI should be regulated at all,” says Brennan. “There are a lot of things we saw with 1047 that we can expect to see replay in New York if this bill is introduced. We should be prepared to see a massive lobbying reaction that industry is going to bring to even the lightest-touch regulation.”

    Wiener and Bores both wish to see regulation at a national level, but in the absence of such legislation, they’ve taken the battle upon themselves. At first it may seem odd for states to take up such important reforms, but California houses the headquarters of the top AI companies, and New York, which has the third-largest state economy in the US, is home to offices for OpenAI and other AI companies. The two states may be well positioned to lead the conversation around regulation. 

    “There is uncertainty at the direction of federal policy with the transition upcoming and around the role of Congress,” says Kohler. “It is likely that states will continue to step up in this area.”

    Wiener’s advice for New York legislators entering the arena of AI regulation? “Buckle up and get ready.”

    What’s next for our privacy?

    MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here.

    Every day, we are tracked hundreds or even thousands of times across the digital world. Cookies and web trackers capture every website link that we click, while code installed in mobile apps tracks every physical location that our devices—and, by extension, we—have visited. All of this is collected, packaged together with other details (compiled from public records, supermarket member programs, utility companies, and more), and used to create highly personalized profiles that are then shared or sold, often without our explicit knowledge or consent. 

    A consensus is growing that Americans need better privacy protections—and that the best way to deliver them would be for Congress to pass comprehensive federal privacy legislation. While the latest iteration of such a bill, the American Privacy Rights Act of 2024, gained more momentum than previously proposed laws, it became so watered down that it lost support from both Republicans and Democrats before it even came to a vote. 

    There have been some privacy wins in the form of limits on what data brokers—third-party companies that buy and sell consumers’ personal information for targeted advertisements, messaging, and other purposes—can do with geolocation data. 

    These are still small steps, though—and they are happening as increasingly pervasive and powerful technologies collect more data than ever. And at the same time, Washington is preparing for a new presidential administration that has attacked the press and other critics, promised to target immigrants for mass deportation, threatened to seek retribution against perceived enemies, and supported restrictive state abortion laws. This is not even to mention the increased collection of our biometric data, especially for facial recognition, and the normalization of its use in all kinds of ways. In this light, it’s no stretch to say our personal data has arguably never been more vulnerable, and the imperative for privacy has never felt more urgent. 

    So what can Americans expect for their personal data in 2025? We spoke to privacy experts and advocates about (some of) what’s on their mind regarding how our digital data might be traded or protected moving forward. 

    Reining in a problematic industry

    In early December, the Federal Trade Commission announced separate settlement agreements with the data brokers Mobilewalla and Gravy Analytics (and its subsidiary Venntel). Finding that the companies had tracked and sold geolocation data from users at sensitive locations like churches, hospitals, and military installations without explicit consent, the FTC banned the companies from selling such data except in specific circumstances. This follows something of a busy year in regulation of data brokers, including multiple FTC enforcement actions against other companies for similar use and sale of geolocation data, as well as a proposed rule from the Justice Department that would prohibit the sale of bulk data to foreign entities. 

    And on the same day that the FTC announced these settlements in December, the Consumer Financial Protection Bureau proposed a new rule that would designate data brokers as consumer reporting agencies, which would trigger stringent reporting requirements and consumer privacy protections. The rule would prohibit the collection and sharing of people’s sensitive information, such as their salaries and Social Security numbers, without “legitimate purposes.” While the rule will still need to undergo a 90-day public comment period, and it’s unclear whether it will move forward under the Trump administration, if it’s finalized it has the power to fundamentally limit how data brokers do business.

    Right now, there just aren’t many limits on how these companies operate—nor, for that matter, clear information on how many data brokerages even exist. Industry watchers estimate there may be 4,000 to 5,000 data brokers around the world, many of which we’ve never heard of—and whose names constantly shift. In California alone, the state’s 2024 Data Broker Registry lists 527 such businesses that have voluntarily registered there, nearly 90 of which also self-reported that they collect geolocation data. 

    All this data is widely available for purchase by anyone who will pay. Marketers buy data to create highly targeted advertisements, and banks and insurance companies do the same to verify identity, prevent fraud, and conduct risk assessments. Law enforcement buys geolocation data to track people’s whereabouts without getting traditional search warrants. Foreign entities can also currently buy sensitive information on members of the military and other government officials. And on people-finder websites, basically anyone can pay for anyone else’s contact details and personal history.  

    Data brokers and their clients defend these transactions by saying that most of this data is anonymized—though it’s questionable whether that can truly be done in the case of geolocation data. Besides, anonymous data can be easily reidentified, especially when it’s combined with other personal information. 

    Digital-rights advocates have spent years sounding the alarm on this secretive industry, especially the ways in which it can harm already marginalized communities, though various types of data collection have sparked consternation across the political spectrum. Representative Cathy McMorris Rodgers, the Republican chair of the House Energy and Commerce Committee, for example, was concerned about how the Centers for Disease Control and Prevention bought location data to evaluate the effectiveness of pandemic lockdowns. Then a study from last year showed how easy (and cheap) it was to buy sensitive data about members of the US military; Senator Elizabeth Warren, a Democrat, called out the national security risks of data brokers in a statement to MIT Technology Review, and Senator John Cornyn, a Republican, later said he was “shocked” when he read about the practice in our story. 

    But it was the 2022 Supreme Court decision ending the constitutional guarantee of legal abortion that spurred much of the federal action last year. Shortly after the Dobbs ruling, President Biden issued an executive order to protect access to reproductive health care; it included instructions for the FTC to take steps preventing information about visits to doctor’s offices or abortion clinics from being sold to law enforcement agencies or state prosecutors.

    The new enforcers

    With Donald Trump taking office in January, and Republicans taking control of both houses of Congress, the fate of the CFPB’s proposed rule—and the CFPB itself—is uncertain. Republicans, the people behind Project 2025, and Elon Musk (who will lead the newly created advisory group known as the Department of Government Efficiency) have long been interested in seeing the bureau “deleted,” as Musk put it on X. That would take an act of Congress, making it unlikely, but there are other ways that the administration could severely curtail its powers. Trump is likely to fire the current director and install a Republican who could rescind existing CFPB rules and stop any proposed rules from moving forward. 

    Meanwhile, the FTC’s enforcement actions are only as good as the enforcers. FTC decisions do not set legal precedent in quite the same way that court cases do, says Ben Winters, a former Department of Justice official and the director of AI and privacy at the Consumer Federation of America, a network of organizations and agencies focused on consumer protection. Instead, they “require consistent [and] additional enforcement to make the whole industry scared of not having an FTC enforcement action against them.” (It’s also worth noting that these FTC settlements are specifically focused on geolocation data, which is just one of the many types of sensitive data that we regularly give up in order to participate in the digital world.)

    Looking ahead, Tiffany Li, a professor at the University of San Francisco School of Law who focuses on AI and privacy law, is worried about “a defanged FTC” that she says would be “less aggressive in taking action against companies.” 

    Lina Khan, the current FTC chair, has been the leader of privacy protection action in the US, notes Li, and she’ll soon be leaving. Andrew Ferguson, Trump’s recently named pick to be the next FTC chair, has come out in strong opposition to data brokers: “This type of data—records of a person’s precise physical locations—is inherently intrusive and revealing of people’s most private affairs,” he wrote in a statement on the Mobilewalla decision, indicating that he is likely to continue action against them. (Ferguson has been serving as a commissioner on the FTC since April 20214.) On the other hand, he has spoken out against using FTC actions as an alternative to privacy legislation passed by Congress. And, of course, this brings us right back around to that other major roadblock: Congress has so far failed to pass such laws—and it’s unclear if the next Congress will either. 

    Movement in the states

    Without federal legislative action, many US states are taking privacy matters into their own hands. 

    In 2025, eight new state privacy laws will take effect, making a total of 25 around the country. A number of other states—like Vermont and Massachusetts—are considering passing their own privacy bills next year, and such laws could, in theory, force national legislation, says Woodrow Hartzog, a technology law scholar at Boston University School of Law. “Right now, the statutes are all similar enough that the compliance cost is perhaps expensive but manageable,” he explains. But if one state passed a law that was different enough from the others, a national law could be the only way to resolve the conflict. Additionally, four states—California, Texas, Vermont, and Oregon—already have specific laws regulating data brokers, including the requirement that they register with the state. 

    Along with new laws, says Justin Brookman, the director of technology policy at Consumer Reports, comes the possibility that “we can put some more teeth on these laws.” 

    Brookman points to Texas, where some of the most aggressive enforcement action at the state level has taken place under its Republican attorney general, Ken Paxton. Even before the state’s new consumer privacy bill went into effect in July, Paxton announced the creation of a special task force focused on enforcing the state’s privacy laws. He has since targeted a number of data brokers—including National Public Data, which exposed millions of sensitive customer records in a data breach in August, as well as companies that sell to them, like Sirius XM. 

    At the same time, though, Paxton has moved to enforce the state’s strict abortion laws in ways that threaten individual privacy. In December, he sued a New York doctor for sending abortion pills to a Texas woman through the mail. While the doctor is theoretically protected by New York’s shield laws, which provide a safeguard from out-of-state prosecution, Paxton’s aggressive action makes it even more crucial that states enshrine data privacy protections into their laws, says Albert Fox Cahn, the executive director of the Surveillance Technology Oversight Project, an advocacy group. “There is an urgent need for states,” he says, “to lock down our resident’s’ data, barring companies from collecting and sharing information in ways that can be weaponized against them by out-of-state prosecutors.” 

    Data collection in the name of “security”

    While privacy has become a bipartisan issue, Republicans, in particular, are interested in “addressing data brokers in the context of national security,” such as protecting the data of military members or other government officials, says Winters. But in his view, it’s the effects on reproductive rights and immigrants that are potentially the “most dangerous” threats to privacy. 

    Indeed, data brokers (including Venntel, the Gravy Analytics subsidiary named in the recent FTC settlement) have sold cell-phone data to Immigration and Customs Enforcement, as well as to Customs and Border Protection. That data has then been used to track individuals for deportation proceedings—allowing the agencies to bypass local and state sanctuary laws that ban local law enforcement from sharing information for immigration enforcement. 

    “The more data that corporations collect, the more data that’s available to governments for surveillance,” warns Ashley Gorski, a senior attorney who works on national security and privacy at the American Civil Liberties Union.

    The ACLU is among a number of organizations that have been pushing for the passage of another federal law related to privacy: the Fourth Amendment Is Not For Sale Act. It would close the so-called “data-broker loophole” that allows law enforcement and intelligence agencies to buy personal information from data brokers without a search warrant. The bill would “dramatically limit the ability of the government to buy Americans’ private data,” Gorski says. It was first introduced in 2021 and passed the House in April 2024, with the support of 123 Republicans and 93 Democrats, before stalling in the Senate. 

    While Gorski is hopeful that the bill will move forward in the next Congress, others are less sanguine about these prospects—and alarmed about other ways that the incoming administration might “co-opt private systems for surveillance purposes,” as Hartzog puts it. So much of our personal information that is “collected for one purpose,” he says, could “easily be used by the government … to track us.” 

    This is especially concerning, adds Winters, given that the next administration has been “very explicit” about wanting to use every tool at its disposal to carry out policies like mass deportations and to exact revenge on perceived enemies. And one possible change, he says, is as simple as loosening the government’s procurement processes to make them more open to emerging technologies, which may have fewer privacy protections. “Right now, it’s annoying to procure anything as a federal agency,” he says, but he expects a more “fast and loose use of commercial tools.” 

    “That’s something we’ve [already] seen a lot,” he adds, pointing to “federal, state, and local agencies using the Clearviews of the world”—a reference to the controversial facial recognition company. 

    The AI wild card

    Underlying all of these debates on potential legislation is the fact that technology companies—especially AI companies—continue to require reams and reams of data, including personal data, to train their machine-learning models. And they’re quickly running out of it. 

    This is something of a wild card in any predictions about personal data. Ideally, says Jennifer King, a privacy and data policy fellow at the Stanford Institute for Human-Centered Artificial Intelligence, the shortage would lead to ways for consumers to directly benefit, perhaps financially, from the value of their own data. But it’s more likely that “there will be more industry resistance against some of the proposed comprehensive federal privacy legislation bills,” she says. “Companies benefit from the status quo.” 

    The hunt for more and more data may also push companies to change their own privacy policies, says Whitney Merrill, a former FTC official who works on data privacy at Asana. Speaking in a personal capacity, she says that companies “have felt the squeeze in the tech recession that we’re in, with the high interest rates,” and that under those circumstances, “we’ve seen people turn around, change their policies, and try to monetize their data in an AI world”—even if it’s at the expense of user privacy. She points to the $60-million-per-year deal that Reddit struck last year to license its content to Google to help train the company’s AI. 

    Earlier this year, the FTC warned companies that it would be “unfair and deceptive” to “surreptitiously” change their privacy policies to allow for the use of user data to train AI. But again, whether or not officials follow up on this depends on those in charge. 

    So what will privacy look like in 2025? 

    While the recent FTC settlements and the CFPB’s proposed rule represent important steps forward in privacy protection—at least when it comes to geolocation data—Americans’ personal information still remains widely available and vulnerable. 

    Rebecca Williams, a senior strategist at the ACLU for privacy and data governance, argues that all of us, as individuals and communities, should take it upon ourselves to do more to protect ourselves and “resist … by opting out” of as much data collection as possible. That means checking privacy settings on accounts and apps, and using encrypted messaging services. 

    Cahn, meanwhile, says he’ll “be striving to protect [his] local community, working to enact safeguards to ensure that we live up to our principles and stated commitments.” One example of such safeguards is a proposed New York City ordinance that would ban the sharing of any location data originating from within the city limits. Hartzog says that kind of local activism has already been effective in pushing for city bans on facial recognition. 

    “Privacy rights are at risk, but they’re not gone, and it’s not helpful to take an overly pessimistic look right now,” says Li, the USF law professor. “We definitely still have privacy rights, and the more that we continue to fight for these rights, the more we’re going to be able to protect our rights.”