Jul 30 2025
What you may have missed about Trump’s AI Action Plan

A number of the executive orders and announcements coming from the White House since Donald Trump returned to office have painted an ambitious vision for America’s AI future—crushing competition with China, abolishing “woke” AI models that suppress conservative speech, jump-starting power-hungry AI data centers. But the details have been sparse. 

The White House’s AI Action Plan, released last week, is meant to fix that. Many of the points in the plan won’t come as a surprise, and you’ve probably heard of the big ones by now. Trump wants to boost the buildout of data centers by slashing environmental rules; withhold funding from states that pass “burdensome AI regulations”; and contract only with AI companies whose models are “free from top-down ideological bias.”

But if you dig deeper, certain parts of the plan that didn’t pop up in any headlines reveal more about where the administration’s AI plans are headed. Here are three of the most important issues to watch. 

Trump is escalating his fight with the Federal Trade Commission

When Americans get scammed, they’re supposed to be helped by the Federal Trade Commission. As I wrote last week, the FTC under President Biden increasingly targeted AI companies that overhyped the accuracy of their systems, as well as deployments of AI it found to have harmed consumers. 

The Trump plan vows to take a fresh look at all the FTC actions under the previous administration as part of an effort to get rid of “onerous” regulation that it claims is hampering AI’s development. The administration may even attempt to repeal some of the FTC’s actions entirely. This would weaken a major AI watchdog agency, but it’s just the latest in the Trump administration’s escalating attacks on the FTC. Read more in my story. 

The White House is very optimistic about AI for science

The opening to the AI Action Plan describes a future where AI is doing everything from discovering new materials and drugs to “unraveling ancient scrolls once thought unreadable” to making breakthroughs in science and math. 

That type of unbounded optimism about AI for scientific discovery echoes what tech companies are promising. Some of that optimism is grounded in reality: AI’s role in predicting protein structures has indeed led to material scientific wins (and just last week, Google DeepMind released a new AI meant to help interpret ancient Latin engravings). But the idea that large language models—essentially very good text prediction machines—will act as scientists in their own right has less merit so far. 

Still, the plan shows that the Trump administration wants to award money to labs trying to make it a reality, even as it has worked to slash the funding the National Science Foundation makes available to human scientists, some of whom are now struggling to complete their research. 

And some of the steps the plan proposes are likely to be welcomed by researchers, like funding to build AI systems that are more transparent and interpretable.

The White House’s messaging on deepfakes is confused

Compared with President Biden’s executive orders on AI, the new action plan is mostly devoid of anything related to making AI safer. 

However, there’s a notable exception: a section in the plan that takes on the harms posed by deepfakes. In May, Trump signed legislation to protect people from nonconsensual sexually explicit deepfakes, a growing concern for celebrities and everyday people alike as generative video gets more advanced and cheaper to use. The law had bipartisan support.

Now, the White House says it’s concerned about the issues deepfakes could pose for the legal system. For example, it says, “fake evidence could be used to attempt to deny justice to both plaintiffs and defendants.” It calls for new standards for deepfake detection and asks the Department of Justice to create rules around it. Legal experts I’ve spoken with are more concerned with a different problem: Lawyers are adopting AI models that make errors such as citing cases that don’t exist, which judges may not catch. This is not addressed in the action plan. 

It’s also worth noting that just days before releasing a plan that targets “malicious deepfakes,” President Trump shared a fake AI-generated video of former president Barack Obama being arrested in the Oval Office.

Overall, the AI Action Plan affirms what President Trump and those in his orbit have long signaled: It’s the defining social and political weapon of our time. They believe that AI, if harnessed correctly, can help them win everything from culture wars to geopolitical conflicts. The right AI, they argue, will help defeat China. Government pressure on leading companies can force them to purge “woke” ideology from their models. 

The plan includes crowd-pleasers—like cracking down on deepfakes—but overall, it reflects how tech giants have cozied up to the Trump administration. The fact that it contains almost no provisions challenging their power shows how their investment in this relationship is paying off.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

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Jul 30 2025
This startup wants to use the Earth as a massive battery

The Texas-based startup Quidnet Energy just completed a test showing it can store energy for up to six months by pumping water underground.

Using water to store electricity is hardly a new concept—pumped hydropower storage has been around for over a century. But the company hopes its twist on the technology could help bring cheap, long-duration energy storage to new places.

In traditional pumped hydro storage facilities, electric pumps move water uphill, into a natural or manmade body of water. Then, when electricity is needed, that water is released and flows downhill past a turbine, generating electricity. Quidnet’s approach instead pumps water down into impermeable rock formations and keeps it under pressure so it flows up when released. “It’s like pumped hydro, upside down,” says CEO Joe Zhou.

Quidnet started a six-month test of its technology in late 2024, pressurizing the system. In June, the company was able to discharge 35 megawatt-hours of energy from the well. There was virtually no self-discharge, meaning no energy loss, Zhou says.

Inexpensive forms of energy storage that can store electricity for weeks or months could help inconsistent electricity sources like wind and solar go further for the grid. And Quidnet’s approach, which uses commercially available equipment, could be deployed quickly and qualify for federal tax credits to help make it even cheaper.

However, there’s still a big milestone ahead: turning the pressurized water back into electricity. The company is currently building a facility with the turbines and support equipment to do that—all the components are available to purchase from established companies. “We don’t need to invent new things based on what we’ve already developed today,” Zhou says. “We can now start just deploying at very, very substantial scales.”

That process will come with energy losses. Energy storage systems are typically measured by their round-trip efficiency: how much of the electricity that’s put into the system is returned at the end as electricity. Modeling suggests that Quidnet’s technology could reach a maximum efficiency of about 65%, Zhou says, though some design choices made to optimize for economics will likely cause the system to land at roughly 50%.

That’s less efficient than lithium-ion batteries, but long-duration systems, if they’re cheap enough, can operate at low efficiencies and still be useful for the grid, says Paul Denholm, a senior research fellow at the National Renewable Energy Laboratory.

“It’s got to be cost-competitive; it all comes down to that,” Denholm says.

Lithium-ion batteries, the fastest-growing technology in energy storage, are the target that new forms of energy storage, like Quidnet’s, must chase. Lithium-ion batteries are about 90% cheaper today than they were 15 years ago. They’ve become a price-competitive alternative to building new natural-gas plants, Denholm says.

When it comes to competing with batteries, one potential differentiator for Quidnet could be government subsidies. While the Trump administration has clawed back funding for clean energy technologies, there’s still an energy storage tax credit, though recently passed legislation added new supply chain restrictions.

Starting in 2026, new energy storage facilities hoping to qualify for tax credits will need to prove that at least 55% of the value of a project’s materials are not from foreign entities of concern. That rules out sourcing batteries from China, which dominates battery production today. Quidnet has a “high level of domestic content” and expects to qualify for tax credits under the new rules, Zhou says.

The facility Quidnet is building is a project with utility partner CPS Energy, and it should come online in early 2026. 

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Jul 30 2025
OpenAI is launching a version of ChatGPT for college students

OpenAI is launching Study Mode, a version of ChatGPT for college students that it promises will act less like a lookup tool and more like a friendly, always-available tutor. It’s part of a wider push by the company to get AI more embedded into classrooms when the new academic year starts in September.

A demonstration for reporters from OpenAI showed what happens when a student asks Study Mode about an academic subject like game theory. The chatbot begins by asking what the student wants to know and then attempts to build an exchange, where the pair work methodically toward the answer together. OpenAI says the tool was built after consulting with pedagogy experts from over 40 institutions.

A handful of college students who were part of OpenAI’s testing cohort—hailing from Princeton, Wharton, and the University of Minnesota—shared positive reviews of Study Mode, saying it did a good job of checking their understanding and adapting to their pace.

The learning approaches that OpenAI has programmed into Study Mode, which are based partially on Socratic methods, appear sound, says Christopher Harris, an educator in New York who has created a curriculum aimed at AI literacy. They might grant educators more confidence about allowing, or even encouraging, their students to use AI. “Professors will see this as working with them in support of learning as opposed to just being a way for students to cheat on assignments,” he says.

But there’s a more ambitious vision behind Study Mode. As demonstrated in OpenAI’s recent partnership with leading teachers’ unions, the company is currently trying to rebrand chatbots as tools for personalized learning rather than cheating. Part of this promise is that AI will act like the expensive human tutors that currently only the most well-off students’ families can typically afford.

“We can begin to close the gap between those with access to learning resources and high-quality education and those who have been historically left behind,” says OpenAI’s head of education. Leah Belsky.

But painting Study Mode as an education equalizer obfuscates one glaring problem. Underneath the hood, it is not a tool trained exclusively on academic textbooks and other approved materials—it’s more like the same old ChatGPT, tuned with a new conversation filter that simply governs how it responds to students, encouraging fewer answers and more explanations. 

This AI tutor, therefore, more resembles what you’d get if you hired a human tutor who has read every required textbook, but also every flawed explanation of the subject ever posted to Reddit, Tumblr, and the farthest reaches of the web. And because of the way AI works, you can’t expect it to distinguish right information from wrong. 

Professors encouraging their students to use it run the risk of it teaching them to approach problems in the wrong way—or worse, being taught material that is fabricated or entirely false. 

Given this limitation, I asked OpenAI if Study Mode is limited to particular subjects. The company said no—students will be able to use it to discuss anything they’d normally talk to ChatGPT about. 

It’s true that access to human tutors—which for certain subjects can cost upward of $200 an hour—is typically for the elite few. The notion that AI models can spread the benefits of tutoring to the masses holds an allure. Indeed, it is backed up by at least some early research that shows AI models can adapt to individual learning styles and backgrounds.

But this improvement comes with a hidden cost. Tools like Study Mode, at least for now, take a shortcut by using large language models’ humanlike conversational style without fixing their inherent flaws. 

OpenAI also acknowledges that this tool won’t prevent a student who’s frustrated and wants an answer from simply going back to normal ChatGPT. “If someone wants to subvert learning, and sort of get answers and take the easier route, that is possible,” Belsky says. 

However, one thing going for Study Mode, the students say, is that it’s simply more fun to study with a chatbot that’s always encouraging you along than to stare at a textbook on Bayesian theorem for the hundredth time. “It’s like the reward signal of like, oh, wait, I can learn this small thing,” says Maggie Wang, a student from Princeton who tested it. The tool is free for now, but Praja Tickoo, a student from Wharton, says it wouldn’t have to be for him to use it. “I think it’s absolutely something I would be willing to pay for,” he says.

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Jul 30 2025
Exclusive: A record-breaking baby has been born from an embryo that’s over 30 years old

A baby boy born over the weekend holds the new record for the “oldest baby.” Thaddeus Daniel Pierce, who arrived on July 26, developed from an embryo that had been in storage for 30 and a half years.

“We had a rough birth but we are both doing well now,” says Lindsey Pierce, his mother. “He is so chill. We are in awe that we have this precious baby!”

Lindsey and her husband, Tim Pierce, who live in London, Ohio, “adopted” the embryo from a woman who had it created in 1994. She says her family and church family think “it’s like something from a sci-fi movie.” 

“The baby has a 30-year-old sister,” she adds. Tim was a toddler when the embryos were first created.

“It’s been pretty surreal,” says Linda Archerd, 62, who donated the embryo. “It’s hard to even believe.”

Three little hopes

The story starts back in the early 1990s. Archerd had been trying—and failing—to get pregnant for six years. She and her husband decided to try IVF, a fairly new technology at the time. “People were [unfamiliar] with it,” says Archerd. “A lot of people were like, what are you doing?”

They did it anyway, and in May 1994, they managed to create four embryos. One of them was transferred to Linda’s uterus. It resulted in a healthy baby girl. “I was so blessed to have a baby,” Archerd says. The remaining three embryos were cryopreserved and kept in a storage tank.

That was 31 years ago. The healthy baby girl is now a 30-year-old woman who has her own 10-year-old daughter. But the other three embryos remained frozen in time.

Archerd originally planned to use the embryos herself. “I always wanted another baby desperately,” she says. “I called them my three little hopes.” Her then husband felt differently, she says. Archerd went on to divorce him, but she won custody of the embryos and kept them in storage, still hopeful she might use them one day, perhaps with another partner.

That meant paying annual storage fees, which increased over time and ended up costing Archerd around a thousand dollars a year, she says. To her, it was worth it. “I always thought it was the right thing to do,” she says. 

Things changed when she started going through menopause, she says. She considered her options. She didn’t want to discard the embryos or donate them for research. And she didn’t want to donate them to another family anonymously—she wanted to meet the parents and any resulting babies. “It’s my DNA; it came from me … and [it’s] my daughter’s sibling,” she says.

Then she found out about embryo “adoption.” This is a type of embryo donation in which both donors and recipients have a say in whom they “place” their embryos with or “adopt” them from. It is overseen by agencies—usually explicitly religious ones—that believe an embryo is morally equivalent to a born human. Archerd is Christian.

There are several agencies that offer these adoption services in the US, but not all of them accept embryos that have been stored for a very long time. That’s partly because those embryos will have been frozen and stored in unfamiliar, old-fashioned ways, and partly because old embryos are thought to be less likely to survive thawing and transfer to successfully develop into a baby.

“So many places wouldn’t even take my information,” says Archerd. Then she came across the Snowflakes program run by the Nightlight Christian Adoptions agency. The agency was willing to accept her embryos, but it needed Archerd’s medical records from the time the embryos had been created, as well as the embryos’ lab records.

So Archerd called the fertility doctor who had treated her decades before. “I still remembered his phone number by heart,” she says. That doctor, now in his 70s, is still practicing at a clinic in Oregon. He dug Archerd’s records out from his basement, she says. “Some of [them] were handwritten,” she adds. Her embryos entered Nightlight’s “matching pool” in 2022.

Making a match

“Our matching process is really driven by the preferences of the placing family,” says Beth Button, executive director of the Snowflakes program. Archerd’s preference was for a married Caucasian, Christian couple living in the US. “I didn’t want them to go out of the country,” says Archerd. “And being Christian is very important to me, because I am.”

It took a while to find a match. Most of the “adopting parents” signed up for the Snowflakes program were already registered at fertility clinics that wouldn’t have accepted the embryos, says Button. “I would say that over 90% of clinics in the US would not have accepted these embryos,” she says.

Expecting parents Tim and Lindsey Pierce.
Lindsey and Tim Pierce at Rejoice Fertility.
COURTESY LINDSEY PIERCE

Archerd’s embryos were assigned to the agency’s Open Hearts program for embryos that are “hard to place,” along with others that have been in storage for a long time or are otherwise thought to be less likely to result in a healthy birth.

Lindsey and Tim Pierce had also signed up for the Open Hearts program. The couple, aged 35 and 34, respectively, had been trying for a baby for seven years and had seen multiple doctors.

Lindsey was researching child adoption when she came across the Snowflakes program. 

When the couple were considering their criteria for embryos they might receive, they decided that they’d be open to any. “We checkmarked anything and everything,” says Tim. That’s how they ended up being matched with Archerd’s embryos. “We thought it was wild,” says Lindsey. “We didn’t know they froze embryos that long ago.”

Lindsey and Tim had registered with Rejoice Fertility, an IVF clinic in Knoxville, Tennessee, run by John Gordon, a reproductive endocrinologist who prides himself on his efforts to reduce the number of embryos in storage. The huge numbers of embryos left in storage tanks was weighing on his conscience, he says, so around six years ago, he set up Rejoice Fertility with the aim of doing things differently.  

“Now we’re here in the belt buckle of the Bible Belt,” says Gordon, who is Reformed Presbyterian. “I’ve changed my mode of practice.” IVF treatments performed at the clinic are designed to create as few excess embryos as possible. The clinic works with multiple embryo adoption agencies and will accept any embryo, no matter how long it has been in storage.

A portrait of Linda Archerd.

COURTESY LINDA ARCHERD

It was his clinic that treated the parents who previously held the record for the longest-stored embryo—in 2022, Rachel and Philip Ridgeway had twins from embryos created more than 30 years earlier. “They’re such a lovely couple,” says Gordon. When we spoke, he was making plans to meet the family for breakfast. The twins are “growing like weeds,” he says with a laugh.

“We have certain guiding principles, and they’re coming from our faith,” says Gordon, although he adds that he sees patients who hold alternative views. One of those principles is that “every embryo deserves a chance at life and that the only embryo that cannot result in a healthy baby is the embryo not given the opportunity to be transferred into a patient.”

That’s why his team will endeavor to transfer any embryo they receive, no matter the age or conditions. That can be challenging, especially when the embryos have been frozen or stored in unusual or outdated ways. “It’s scary for people who don’t know how to do it,” says Sarah Atkinson, lab supervisor and head embryologist at Rejoice Fertility. “You don’t want to kill someone’s embryos if you don’t know what you’re doing.”

Cumbersome and explosive

In the early days of IVF, embryos earmarked for storage were slow-frozen. This technique involves gradually lowering the temperature of the embryos. But because slow freezing can cause harmful ice crystals to form, clinics switched in the 2000s to a technique called vitrification, in which the embryos are placed in thin plastic tubes called straws and lowered into tanks of liquid nitrogen. This rapidly freezes the embryos and converts them into a glass-like state. 

The embryos can later be thawed by removing them from the tanks and rapidly—within two seconds—plunging them into warm “thaw media,” says Atkinson. Thawing slow-frozen embryos is more complicated. And the exact thawing method required varies, depending on how the embryos were preserved and what they were stored in. Some of the devices need to be opened while they are inside the storage tank, which can involve using forceps, diamond-bladed knives, and other tools in the liquid nitrogen, says Atkinson.

Sarah Atkinson, lab supervisor and head embryologist at Rejoice Fertility, directly injects sperm into two eggs to fertilize them.
COURTESY OF SARAH ATKINSON AT REJOICE FERTILITY.

Recently, she was tasked with retrieving embryos that had been stored inside a glass vial. The vial was made from blown glass and had been heat-sealed with the embryo inside. Atkinson had to use her diamond-bladed knife to snap open the seal inside the nitrogen tank. It was fiddly work, and when the device snapped, a small shard of glass flew out and hit Atkinson’s face. “Hit me on the cheek, cut my cheek, blood running down my face, and I’m like, Oh shit,” she says. Luckily, she had her safety goggles on. And the embryos survived, she adds.

The two embryos that were transferred to Lindsey Pierce.

Atkinson has a folder in her office with notes she’s collected on various devices over the years. She flicks through it over a video call and points to the notes she made about the glass vial. “Might explode; wear face shield and eye protection,” she reads. A few pages later, she points to another embryo-storage device. “You have to thaw this one in your fingers,” she tells me. “I don’t like it.”

The record-breaking embryos had been slow-frozen and stored in a plastic vial, says Atkinson. Thawing them was a cumbersome process. But all three embryos survived it.

The Pierces had to travel from their home in Ohio to the clinic in Tennessee five times over a two-week period. “It was like a five-hour drive,” says Lindsey. One of the three embryos stopped growing. The other two were transferred to Lindsey’s uterus on November 14, she says. And one developed into a fetus.

Now that the baby has arrived, Archerd is keen to meet him. “The first thing that I noticed when Lindsey sent me his pictures is how much he looks like my daughter when she was a baby,” she says. “I pulled out my baby book and compared them side by side, and there is no doubt that they are siblings.”

She doesn’t yet have plans to meet the baby, but doing so would be “a dream come true,” she says. “I wish that they didn’t live so far away from me … He is perfect!”

“We didn’t go into it thinking we would break any records,” says Lindsey. “We just wanted to have a baby.”

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Jul 29 2025
Chinese universities want students to use more AI, not less

Just two years ago, Lorraine He, now a 24-year-old law student,  was told to avoid using AI for her assignments. At the time, to get around a national block on ChatGPT, students had to buy a mirror-site version from a secondhand marketplace. Its use was common, but it was at best tolerated and more often frowned upon. Now, her professors no longer warn students against using AI. Instead, they’re encouraged to use it—as long as they follow best practices.

She is far from alone. Just like those in the West, Chinese universities are going through a quiet revolution. According to a recent survey by the Mycos Institute, a Chinese higher-education research group, the use of generative AI on campus has become nearly universal. The same survey reports that just 1% of university faculty and students in China reported never using AI tools in their studies or work. Nearly 60% said they used them frequently—either multiple times a day or several times a week.

However, there’s a crucial difference. While many educators in the West see AI as a threat they have to manage, more Chinese classrooms are treating it as a skill to be mastered. In fact, as the Chinese-developed model DeepSeek gains in popularity globally, people increasingly see it as a source of national pride. The conversation in Chinese universities has gradually shifted from worrying about the implications for academic integrity to encouraging literacy, productivity, and staying ahead. 

The cultural divide is even more apparent in public sentiment. A report on global AI attitudes from Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI) found that China leads the world in enthusiasm. About 80% of Chinese respondents said they were “excited” about new AI services—compared with just 35% in the US and 38% in the UK.

“This attitude isn’t surprising,” says Fang Kecheng, a professor in communications at the Chinese University of Hong Kong. “There’s a long tradition in China of believing in technology as a driver of national progress, tracing back to the 1980s, when Deng Xiaoping was already saying that science and technology are primary productive forces.”

From taboo to toolkit

Liu Bingyu, one of He’s professors at the China University of Political Science and Law, says AI can act as “instructor, brainstorm partner, secretary, and devil’s advocate.” She added a full session on AI guidelines to her lecture series this year, after the university encouraged “responsible and confident” use of AI. 

Liu recommends that students use generative AI to write literature reviews, draft abstracts, generate charts, and organize thoughts. She’s created slides that lay out detailed examples of good and bad prompts, along with one core principle: AI can’t replace human judgment. “Only high-quality input and smart prompting can lead to good results,” she says.

“The ability to interact with machines is one of the most important skills in today’s world,” Liu told her class. “And instead of having students do it privately, we should talk about it out in the open.”

This reflects a growing trend across the country. MIT Technology Review reviewed the AI strategies of 46 top Chinese universities and found that almost all of them have added interdisciplinary AI general‑education classes, AI related degree programs and AI literacy modules in the past year. Tsinghua, for example, is establishing a new undergraduate general education college to train students in AI plus another traditional discipline, like biology, healthcare, science, or humanities.

Major institutions like Remin, Nanjing, and Fudan Universities have rolled out general-access AI courses and degree programs that are open to all students, not reserved for computer science majors like the traditional machine-learning classes. At Zhejiang University, an introductory AI class will become mandatory for undergraduates starting in 2024. 

Lin Shangxin, principal of Renmin University of China recently told local media that AI was an “unprecedented opportunity” for humanities and social sciences. “Intead of a challenge, I believe AI would empower humanities studies,” Lin said told The Paper.

The collective action echoes a central government push. In April 2025, the Ministry of Education released new national guidelines calling for sweeping “AI+ education” reforms, aimed at cultivating critical thinking, digital fluency, and real‐world skills at all education levels. Earlier this year, the Beijing municipal government mandated AI education across all schools in the city—from universities to K–12.

Fang believes that more formal AI literacy education will help bridge an emerging divide between students. “There’s a big gap in digital literacy,” he says. “Some students are fluent in AI tools. Others are lost.”

Building the AI university

In the absence of Western tools like ChatGPT and Claude, many Chinese universities have begun deploying local versions of DeepSeek on campus servers to support students. Many top universities have deployed their own locally hosted versions of Deepseek. These campus-specific AI systems–often referred to as the “full-blood version” of Deepseek—offer longer context windows, unlimited dialogue rounds and broader functionality than public-facing free versions. 

This mirrors a broader trend in the West, where companies like OpenAI and Anthropic are rolling out campus-wide education tiers—OpenAI recently offered free ChatGPT Plus to all U.S. and Canadian college students, while Anthropic launched Claude for Education with partners like Northeastern and LSE. But in China, the initiative is typically university-led rather than driven by the companies themselves.

The goal, according to Zhejiang University, is to offer students full access to AI tools so they can stay up to date with the fast-changing technology. Students can use their ID to access the models for free. 

Yanyan Li and Meifang Zhuo, two researchers at Warwick University who have studied students’ use of AI at universities in the UK, believe that AI literacy education has become crucial to students’ success. 

With their colleague Gunisha Aggarwal, they conducted focus groups including college students from different backgrounds and levels to find out how AI is used in academic studies. They found that students’ knowledge of how to use AI comes mainly from personal exploration. “While most students understand that AI output is not always trustworthy, we observed a lot of anxiety on how to use it right,” says Li.

“The goal shouldn’t be preventing students from using AI but guiding them to harness it for effective learning and higher-order thinking,” says Zhuo. 

That lesson has come slowly. A student at Central China Normal University in Wuhan told MIT Technology Review that just a year ago, most of his classmates paid for mirror websites of ChatGPT, using VPNs or semi-legal online marketplaces to access Western models. “Now, everyone just uses DeepSeek and Doubao,” he said. “It’s cheaper, it works in Chinese, and no one’s worried about getting flagged anymore.”

Still, even with increased institutional support, many students feel anxious about whether they’re using AI correctly—or ethically. The use of AI detection tools has created an informal gray economy, where students pay hundreds of yuan to freelancers promising to “AI-detection-proof” their writing, according to a Rest of World report. Three students told MIT Technology Review that this environment has created confusion, stress, and increased anxiety. Across the board, they said they appreciate it when their professor offers clear policies and practical advice, not just warnings.

He, the law student in Beijing, recently joined a career development group to learn more AI skills to prepare for the job market. To many like her, understanding how to use AI better is not just a studying hack but a necessary skill in China’s fragile job market. Eighty percent of job openings available to fresh graduates listed AI-related skills as a plus in 2025, according to a report by the Chinese media outlet YiCai. In a slowed-down economy and a competitive job market, many students see AI as a lifeline. 

 “We need to rethink what is considered ‘original work’ in the age of AI” says Zhuo, “and universities are a crucial site of that conversation”.

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Jul 27 2025
What role should oil and gas companies play in climate tech?

This week, I have a new story out about Quaise, a geothermal startup that’s trying to commercialize new drilling technology. Using a device called a gyrotron, the company wants to drill deeper, cheaper, in an effort to unlock geothermal power anywhere on the planet. (For all the details, check it out here.) 

For the story, I visited Quaise’s headquarters in Houston. I also took a trip across town to Nabors Industries, Quaise’s investor and tech partner and one of the biggest drilling companies in the world. 

Standing on top of a drilling rig in the backyard of Nabors’s headquarters, I couldn’t stop thinking about the role oil and gas companies are playing in the energy transition. This industry has resources and energy expertise—but also a vested interest in fossil fuels. Can it really be part of addressing climate change?

The relationship between Quaise and Nabors is one that we see increasingly often in climate tech—a startup partnering up with an established company in a similar field. (Another one that comes to mind is in the cement industry, where Sublime Systems has seen a lot of support from legacy players including Holcim, one of the biggest cement companies in the world.) 

Quaise got an early investment from Nabors in 2021, to the tune of $12 million. Now the company also serves as a technical partner for the startup. 

“We are agnostic to what hole we’re drilling,” says Cameron Maresh, a project engineer on the energy transition team at Nabors Industries. The company is working on other investments and projects in the geothermal industry, Maresh says, and the work with Quaise is the culmination of a yearslong collaboration: “We’re just truly excited to see what Quaise can do.”

From the outside, this sort of partnership makes a lot of sense for Quaise. It gets resources and expertise. Meanwhile, Nabors is getting involved with an innovative company that could represent a new direction for geothermal. And maybe more to the point, if fossil fuels are to be phased out, this deal gives the company a stake in next-generation energy production.

There is so much potential for oil and gas companies to play a productive role in addressing climate change. One report from the International Energy Agency examined the role these legacy players could take:  “Energy transitions can happen without the engagement of the oil and gas industry, but the journey to net zero will be more costly and difficult to navigate if they are not on board,” the authors wrote. 

In the agency’s blueprint for what a net-zero emissions energy system could look like in 2050, about 30% of energy could come from sources where the oil and gas industry’s knowledge and resources are useful. That includes hydrogen, liquid biofuels, biomethane, carbon capture, and geothermal. 

But so far, the industry has hardly lived up to its potential as a positive force for the climate. Also in that report, the IEA pointed out that oil and gas producers made up only about 1% of global investment in climate tech in 2022. Investment has ticked up a bit since then, but still, it’s tough to argue that the industry is committed. 

And now that climate tech is falling out of fashion with the government in the US, I’d venture to guess that we’re going to see oil and gas companies increasingly pulling back on their investments and promises. 

BP recently backtracked on previous commitments to cut oil and gas production and invest in clean energy. And last year the company announced that it had written off $1.1 billion in offshore wind investments in 2023 and wanted to sell other wind assets. Shell closed down all its hydrogen fueling stations for vehicles in California last year. (This might not be all that big a loss, since EVs are beating hydrogen by a huge margin in the US, but it’s still worth noting.) 

So oil and gas companies are investing what amounts to pennies and often backtrack when the political winds change direction. And, let’s not forget, fossil-fuel companies have a long history of behaving badly. 

In perhaps the most notorious example, scientists at Exxon modeled climate change in the 1970s, and their forecasts turned out to be quite accurate. Rather than publish that research, the company downplayed how climate change might affect the planet. (For what it’s worth, company representatives have argued that this was less of a coverup and more of an internal discussion that wasn’t fit to be shared outside the company.) 

While fossil fuels are still part of our near-term future, oil and gas companies, and particularly producers, would need to make drastic changes to align with climate goals—changes that wouldn’t be in their financial interest. Few seem inclined to really take the turn needed. 

As the IEA report puts it:  “In practice, no one committed to change should wait for someone else to move first.”

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

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Jul 27 2025
The deadly saga of the controversial gene therapy Elevidys

It has been a grim few months for the Duchenne muscular dystrophy (DMD) community. There had been some excitement when, a couple of years ago, a gene therapy for the disorder was approved by the US Food and Drug Administration for the first time. That drug, Elevidys, has now been implicated in the deaths of two teenage boys.

The drug’s approval was always controversial—there was a lack of evidence that it actually worked, for starters. But the agency that once rubber-stamped the drug has now turned on its manufacturer, Sarepta Therapeutics. In a remarkable chain of events, the FDA asked the company to stop shipping the drug on July 18. Sarepta refused to comply.

In the days since, the company has acquiesced. But its reputation has already been hit. And the events have dealt a devastating blow to people desperate for treatments that might help them, their children, or other family members with DMD.

DMD is a rare genetic disorder that causes muscles to degenerate over time. It’s caused by a mutation in a gene that codes for a protein called dystrophin. That protein is essential for muscles—without it, muscles weaken and waste away. The disease mostly affects boys, and symptoms usually start in early childhood.

At first, affected children usually start to find it hard to jump or climb stairs. But as the disease progresses, other movements become difficult too. Eventually, the condition might affect the heart and lungs. The life expectancy of a person with DMD has recently improved, but it is still only around 30 or 40 years. There is no cure. It’s a devastating diagnosis.

Elevidys was designed to replace missing dystrophin with a shortened, engineered version of the protein. In June 2023, the FDA approved the therapy for eligible four- and five-year-olds. It came with a $3.2 million price tag.

The approval was celebrated by people affected by DMD, says Debra Miller, founder of CureDuchenne, an organization that funds research into the condition and offers support to those affected by it. “We’ve not had much in the way of meaningful therapies,” she says. “The excitement was great.”

But the approval was controversial. It came under an “accelerated approval” program that essentially lowers the bar of evidence for drugs designed to treat “serious or life-threatening diseases where there is an unmet medical need.”

Elevidys was approved because it appeared to increase levels of the engineered protein in patients’ muscles. But it had not been shown to improve patient outcomes: It had failed a randomized clinical trial.

The FDA approval was granted on the condition that Sarepta complete another clinical trial. The topline results of that trial were described in October 2023 and were published in detail a year later. Again, the drug failed to meet its “primary endpoint”—in other words, it didn’t work as well as hoped.

In June 2024, the FDA expanded the approval of Elevidys. It granted traditional approval for the drug to treat people with DMD who are over the age of four and can walk independently, and another accelerated approval for those who can’t.

Some experts were appalled at the FDA’s decision—even some within the FDA disagreed with it. But things weren’t so simple for people living with DMD. I spoke to some parents of such children a couple of years ago. They pointed out that drug approvals can help bring interest and investment to DMD research. And, above all, they were desperate for any drug that might help their children. They were desperate for hope.

Unfortunately, the treatment does not appear to be delivering on that hope. There have always been questions over whether it works. But now there are serious questions over how safe it is. 

In March 2025, a 16-year-old boy died after being treated with Elevidys. He had developed acute liver failure (ALF) after having the treatment, Sarepta said in a statement. On June 15, the company announced a second death—a 15-year-old who also developed ALF following Elevidys treatment. The company said it would pause shipments of the drug, but only for patients who are not able to walk.

The following day, Sarepta held an online presentation in which CEO Doug Ingram said that the company was exploring ways to make the treatment safer, perhaps by treating recipients with another drug that dampens their immune systems. But that same day, the company announced that it was laying off 500 employees—36% of its workforce. Sarepta did not respond to a request for comment.

On June 24, the FDA announced that it was investigating the risks of serious outcomes “including hospitalization and death” associated with Elevidys, and “evaluating the need for further regulatory action.”

There was more tragic news on July 18, when there were reports that a third patient had died following a Sarepta treatment. This patient, a 51-year-old, hadn’t been taking Elevidys but was enrolled in a clinical trial for a different Sarepta gene therapy designed to treat limb-girdle muscular dystrophy. The same day, the FDA asked Sarepta to voluntarily pause all shipments of Elevidys. Sarepta refused to do so.

The refusal was surprising, says Michael Kelly, chief scientific officer at CureDuchenne: “It was an unusual step to take.”

After significant media coverage, including reporting that the FDA was “deeply troubled” by the decision and would use its “full regulatory authority,” Sarepta backed down a few days later. On July 21, the company announced its decision to “voluntarily and temporarily” pause all shipments of Elevidys in the US.

Sarepta says it will now work with the FDA to address safety and labeling concerns. But in the meantime, the saga has left the DMD community grappling with “a mix of disappointment and concern,” says Kelly. Many are worried about the risks of taking the treatment. Others are devastated that they are no longer able to access it.

Miller says she knows of families who have been working with their insurance providers to get authorization for the drug. “It’s like the rug has been pulled out from under them,” she says. Many families have no other treatment options. “And we know what happens when you do nothing with Duchenne,” she says. Others, particularly those with teenage children with DMD, are deciding against trying the drug, she adds.

The decision over whether to take Elevidys was already a personal one based on several factors, he says. People with DMD and their families deserve clear and transparent information about the treatment in order to make that decision.

The FDA’s decision to approve Elevidys was made on limited data, says Kelly. But as things stand today, over 900 people have been treated with Elevidys. “That gives the FDA… an opportunity to look at real data and make informed decisions,” he says.

“Families facing Duchenne do not have time to waste,” Kelly says. “They must navigate a landscape where hope is tempered by the realities of medical complexity.”

A version of this article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

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Jul 27 2025
How nonprofits and academia are stepping up to salvage US climate programs

Nonprofits are striving to preserve a US effort to modernize greenhouse-gas measurements, amid growing fears that the Trump administration’s dismantling of federal programs will obscure the nation’s contributions to climate change.

The Data Foundation, a Washington, DC, nonprofit that advocates for open data, is fundraising for an initiative that will coordinate efforts among nonprofits, technical experts, and companies to improve the accuracy and accessibility of climate emissions information. It will build on an effort to improve the collection of emissions data that former president Joe Biden launched in 2023—and which President Trump nullified on his first day in office. 

The initiative will help prioritize responses to changes in federal greenhouse-gas monitoring and measurement programs, but the Data Foundation stresses that it will primarily serve a “long-standing need for coordination” of such efforts outside of government agencies.

The new greenhouse-gas coalition is one of a growing number of nonprofit and academic groups that have spun up or shifted focus to keep essential climate monitoring and research efforts going amid the Trump administration’s assault on environmental funding, staffing, and regulations. Those include efforts to ensure that US scientists can continue to contribute to the UN’s major climate report and publish assessments of the rising domestic risks of climate change. Otherwise, the loss of these programs will make it increasingly difficult for communities to understand how more frequent or severe wildfires, droughts, heat waves, and floods will harm them—and how dire the dangers could become. 

Few believe that nonprofits or private industry can come close to filling the funding holes that the Trump administration is digging. But observers say it’s essential to try to sustain efforts to understand the risks of climate change that the federal government has historically overseen, even if the attempts are merely stopgap measures. 

If we give up these sources of emissions data, “we’re flying blind,” says Rachel Cleetus, senior policy director with the climate and energy program at the Union of Concerned Scientists. “We’re deliberating taking away the very information that would help us understand the problem and how to address it best.”

Improving emissions estimates

The Environmental Protection Agency, the National Oceanic and Atmospheric Administration, the US Forest Service, and other agencies have long collected information about greenhouse gases in a variety of ways. These include self-reporting by industry; shipboard, balloon, and aircraft readings of gas concentrations in the atmosphere; satellite measurements of the carbon dioxide and methane released by wildfires; and on-the-ground measurements of trees. The EPA, in turn, collects and publishes the data from these disparate sources as the Inventory of US Greenhouse Gas Emissions and Sinks.

But that report comes out on a two-year lag, and studies show that some of the estimates it relies on could be way off—particularly the self-reported ones.

A recent analysis using satellites to measure methane pollution from four large landfills found they produce, on average, six times more emissions than the facilities had reported to the EPA. Likewise, a 2018 study in Science found that the actual methane leaks from oil and gas infrastructure were about 60% higher than the self-reported estimates in the agency’s inventory.

The Biden administration’s initiative—the National Strategy to Advance an Integrated US Greenhouse Gas Measurement, Monitoring, and Information System—aimed to adopt state-of-the-art tools and methods to improve the accuracy of these estimates, including satellites and other monitoring technologies that can replace or check self-reported information.

The administration specifically sought to achieve these improvements through partnerships between government, industry, and nonprofits. The initiative called for the data collected across groups to be published to an online portal in formats that would be accessible to policymakers and the public.

Moving toward a system that produces more current and reliable data is essential for understanding the rising risks of climate change and tracking whether industries are abiding by government regulations and voluntary climate commitments, says Ben Poulter, a former NASA scientist who coordinated the Biden administration effort as a deputy director in the Office of Science and Technology Policy.

“Once you have this operational system, you can provide near-real-time information that can help drive climate action,” Poulter says. He is now a senior scientist at Spark Climate Solutions, a nonprofit focused on accelerating emerging methods of combating climate change, and he is advising the Data Foundation’s Climate Data Collaborative, which is overseeing the new greenhouse-gas initiative. 

Slashed staffing and funding  

But the momentum behind the federal strategy deflated when Trump returned to office. On his first day, he signed an executive order that effectively halted it. The White House has since slashed staffing across the agencies at the heart of the effort, sought to shut down specific programs that generate emissions data, and raised uncertainties about the fate of numerous other program components. 

In April, the administration missed a deadline to share the updated greenhouse-gas inventory with the United Nations, for the first time in three decades, as E&E News reported. It eventually did release the report in May, but only after the Environmental Defense Fund filed a Freedom of Information Act request.

There are also indications that the collection of emissions data might be in jeopardy. In March, the EPA said it would “reconsider” the Greenhouse Gas Reporting Program, which requires thousands of power plants, refineries, and other industrial facilities to report emissions each year.

In addition, the tax and spending bill that Trump signed into law earlier this month rescinds provisions in Biden’s Inflation Reduction Act that provided incentives or funding for corporate greenhouse-gas reporting and methane monitoring. 

Meanwhile, the White House has also proposed slashing funding for the National Oceanic and Atmospheric Administration and shuttering a number of its labs. Those include the facility that supports the Mauna Loa Observatory in Hawaii, the world’s longest-running carbon dioxide measuring program, as well as the Global Monitoring Laboratory, which operates a global network of collection flasks that capture air samples used to measure concentrations of nitrous oxide, chlorofluorocarbons, and other greenhouse gases.

Under the latest appropriations negotiations, Congress seems set to spare NOAA and other agencies the full cuts pushed by the Trump administration, but that may or may not protect various climate programs within them. As observers have noted, the loss of experts throughout the federal government, coupled with the priorities set by Trump-appointed leaders of those agencies, could still prevent crucial emissions data from being collected, analyzed, and published.

“That’s a huge concern,” says David Hayes, a professor at the Stanford Doerr School of Sustainability, who previously worked on the effort to upgrade the nation’s emissions measurement and monitoring as special assistant to President Biden for climate policy. It’s not clear “whether they’re going to continue and whether the data availability will drop off.”

‘A natural disaster’

Amid all these cutbacks and uncertainties, those still hoping to make progress toward an improved system for measuring greenhouse gases have had to adjust their expectations: It’s now at least as important to simply preserve or replace existing federal programs as it is to move toward more modern tools and methods.

But Ryan Alexander, executive director of the Data Foundation’s Climate Data Collaborative, is optimistic that there will be opportunities to do both. 

She says the new greenhouse-gas coalition will strive to identify the highest-priority needs and help other nonprofits or companies accelerate the development of new tools or methods. It will also aim to ensure that these organizations avoid replicating one another’s efforts and deliver data with high scientific standards, in open and interoperable formats. 

The Data Foundation declines to say what other nonprofits will be members of the coalition or how much money it hopes to raise, but it plans to make a formal announcement in the coming weeks. 

Nonprofits and companies are already playing a larger role in monitoring emissions, including organizations like Carbon Mapper, which operates satellites and aircraft that detect and measure methane emissions from particular facilities. The EDF also launched a satellite last year, known as MethaneSAT, that could spot large and small sources of emissions—though it lost power earlier this month and probably cannot be recovered. 

Alexander notes that shifting from self-reported figures to observational technology like satellites could not just replace but perhaps also improve on the EPA reporting program that the Trump administration has moved to shut down.

Given the “dramatic changes” brought about by this administration, “the future will not be the past,” she says. “This is like a natural disaster. We can’t think about rebuilding in the way that things have been in the past. We have to look ahead and say, ‘What is needed? What can people afford?’”

Organizations can also use this moment to test and develop emerging technologies that could improve greenhouse-gas measurements, including novel sensors or artificial intelligence tools, Hayes says. 

“We are at a time when we have these new tools, new technologies for measurement, measuring, and monitoring,” he says. “To some extent it’s a new era anyway, so it’s a great time to do some pilot testing here and to demonstrate how we can create new data sets in the climate area.”

Saving scientific contributions

It’s not just the collection of emissions data that nonprofits and academic groups are hoping to save. Notably, the American Geophysical Union and its partners have taken on two additional climate responsibilities that traditionally fell to the federal government.

The US State Department’s Office of Global Change historically coordinated the nation’s contributions to the UN Intergovernmental Panel on Climate Change’s major reports on climate risks, soliciting and nominating US scientists to help write, oversee, or edit sections of the assessments. The US Global Change Research Program, an interagency group that ran much of the process, also covered the cost of trips to a series of in-person meetings with international collaborators. 

But the US government seems to have relinquished any involvement as the IPCC kicks off the process for the Seventh Assessment Report. In late February, the administration blocked federal scientists including NASA’s Katherine Calvin, who was previously selected as a cochair for one of the working groups, from attending an early planning meeting in China. (Calvin was the agency’s chief scientist at the time but was no longer serving in that role as of April, according to NASA’s website.)

The agency didn’t respond to inquiries from interested scientists after the UN panel issued a call for nominations in March, and it failed to present a list of nominations by the deadline in April, scientists involved in the process say. The Trump administration also canceled funding for the Global Change Research Program and, earlier this month, fired the last remaining staffers working at the Office of Global Change.

In response, 10 universities came together in March to form the US Academic Alliance for the IPCC, in partnership with the AGU, to request and evalute applications from US researchers. The universities—which include Yale, Princeton, and the University of California, San Diego—together nominated nearly 300 scientists, some of whom the IPCC has since officially selected. The AGU is now conducting a fundraising campaign to help pay for travel expenses. 

Pamela McElwee, a professor at Rutgers who helped establish the academic coalition, says it’s crucial for US scientists to continue participating in the IPCC process.

“It is our flagship global assessment report on the state of climate, and it plays a really important role in influencing country policies,” she says. “To not be part of it makes it much more difficult for US scientists to be at the cutting edge and advance the things we need to do.” 

The AGU also stepped in two months later, after the White House dismissed hundreds of researchers working on the National Climate Assessment, an annual report analyzing the rising dangers of climate change across the country. The AGU and American Meteorological Society together announced plans to publish a “special collection” to sustain the momentum of that effort.

“It’s incumbent on us to ensure our communities, our neighbors, our children are all protected and prepared for the mounting risks of climate change,” said Brandon Jones, president of the AGU, in an earlier statement.

The AGU declined to discuss the status of the project.

Stopgap solution

The sheer number of programs the White House is going after will require organizations to make hard choices about what they attempt to save and how they go about it. Moreover, relying entirely on nonprofits and companies to take over these federal tasks is not viable over the long term. 

Given the costs of these federal programs, it could prove prohibitive to even keep a minimum viable version of some essential monitoring systems and research programs up and running. Dispersing across various organizations the responsibility of calculating the nation’s emissions sources and sinks also creates concerns about the scientific standards applied and the accessibility of that data, Cleetus says. Plus, moving away from the records that NOAA, NASA, and other agencies have collected for decades would break the continuity of that data, undermining the ability to detect or project trends.

More basically, publishing national emissions data should be a federal responsibility, particularly for the government of the world’s second-largest climate polluter, Cleetus adds. Failing to calculate and share its contributions to climate change sidesteps the nation’s global responsibilities and sends a terrible signal to other countries. 

Poulter stresses that nonprofits and the private sector can do only so much, for so long, to keep these systems up and running.

“We don’t want to give the impression that this greenhouse-gas coalition, if it gets off the ground, is a long-term solution,” he says. “But we can’t afford to have gaps in these data sets, so somebody needs to step in and help sustain those measurements.”

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Jul 25 2025
America’s AI watchdog is losing its bite

Most Americans encounter the Federal Trade Commission only if they’ve been scammed: It handles identity theft, fraud, and stolen data. During the Biden administration, the agency went after AI companies for scamming customers with deceptive advertising or harming people by selling irresponsible technologies. With yesterday’s announcement of President Trump’s AI Action Plan, that era may now be over. 

In the final months of the Biden administration under chair Lina Khan, the FTC levied a series of high-profile fines and actions against AI companies for overhyping their technology and bending the truth—or in some cases making claims that were entirely false.

It found that the security giant Evolv lied about the accuracy of its AI-powered security checkpoints, which are used in stadiums and schools but failed to catch a seven-inch knife that was ultimately used to stab a student. It went after the facial recognition company Intellivision, saying the company made unfounded claims that its tools operated without gender or racial bias. It fined startups promising bogus “AI lawyer” services and one that sold fake product reviews generated with AI.

These actions did not result in fines that crippled the companies, but they did stop them from making false statements and offered customers ways to recover their money or get out of contracts. In each case, the FTC found, everyday people had been harmed by AI companies that let their technologies run amok.

The plan released by the Trump administration yesterday suggests it believes these actions went too far. In a section about removing “red tape and onerous regulation,” the White House says it will review all FTC actions taken under the Biden administration “to ensure that they do not advance theories of liability that unduly burden AI innovation.” In the same section, the White House says it will withhold AI-related federal funding from states with “burdensome” regulations.

This move by the Trump administration is the latest in its evolving attack on the agency, which provides a significant route of redress for people harmed by AI in the US. It’s likely to result in faster deployment of AI with fewer checks on accuracy, fairness, or consumer harm.

Under Khan, a Biden appointee, the FTC found fans in unexpected places. Progressives called for it to break up monopolistic behavior in Big Tech, but some in Trump’s orbit, including Vice President JD Vance, also supported Khan in her fights against tech elites, albeit for the different goal of ending their supposed censorship of conservative speech. 

But in January, with Khan out and Trump back in the White House, this dynamic all but collapsed. Trump released an executive order in February promising to “rein in” independent agencies like the FTC that wage influence without consulting the president. The next month, he started taking that vow to—and past—its legal limits.

In March, he fired the only two Democratic commissioners at the FTC. On July 17 a federal court ruled that one of those firings, of commissioner Rebecca Slaughter, was illegal given the independence of the agency, which restored Slaughter to her position (the other fired commissioner, Alvaro Bedoya, opted to resign rather than battle the dismissal in court, so his case was dismissed). Slaughter now serves as the sole Democrat.

In naming the FTC in its action plan, the White House now goes a step further, painting the agency’s actions as a major obstacle to US victory in the “arms race” to develop better AI more quickly than China. It promises not just to change the agency’s tack moving forward, but to review and perhaps even repeal AI-related sanctions it has imposed in the past four years.

How might this play out? Leah Frazier, who worked at the FTC for 17 years before leaving in May and served as an advisor to Khan, says it’s helpful to think about the agency’s actions against AI companies as falling into two areas, each with very different levels of support across political lines. 

The first is about cases of deception, where AI companies mislead consumers. Consider the case of Evolv, or a recent case announced in April where the FTC alleges that a company called Workado, which offers a tool to detect whether something was written with AI, doesn’t have the evidence to back up its claims. Deception cases enjoyed fairly bipartisan support during her tenure, Frazier says.

“Then there are cases about responsible use of AI, and those did not seem to enjoy too much popular support,” adds Frazier, who now directs the Digital Justice Initiative at the Lawyers’ Committee for Civil Rights Under Law. These cases don’t allege deception; rather, they charge that companies have deployed AI in a way that harms people.

The most serious of these, which resulted in perhaps the most significant AI-related action ever taken by the FTC and was investigated by Frazier, was announced in 2023. The FTC banned Rite Aid from using AI facial recognition in its stores after it found the technology falsely flagged people, particularly women and people of color, as shoplifters. “Acting on false positive alerts,” the FTC wrote, Rite Aid’s employees “followed consumers around its stores, searched them, ordered them to leave, [and] called the police to confront or remove consumers.”

The FTC found that Rite Aid failed to protect people from these mistakes, did not monitor or test the technology, and did not properly train employees on how to use it. The company was banned from using facial recognition for five years. 

This was a big deal. This action went beyond fact-checking the deceptive promises made by AI companies to make Rite Aid liable for how its AI technology harmed consumers. These types of responsible-AI cases are the ones Frazier imagines might disappear in the new FTC, particularly if they involve testing AI models for bias.

“There will be fewer, if any, enforcement actions about how companies are deploying AI,” she says. The White House’s broader philosophy toward AI, referred to in the plan, is a “try first” approach that attempts to propel faster AI adoption everywhere from the Pentagon to doctor’s offices. The lack of FTC enforcement that is likely to ensue, Frazier says, “is dangerous for the public.”

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Jul 25 2025
Trump’s AI Action Plan is a distraction

On Wednesday, President Trump issued three executive orders, delivered a speech, and released an action plan, all on the topic of continuing American leadership in AI. 

The plan contains dozens of proposed actions, grouped into three “pillars”: accelerating innovation, building infrastructure, and leading international diplomacy and security. Some of its recommendations are thoughtful even if incremental, some clearly serve ideological ends, and many enrich big tech companies, but the plan is just a set of recommended actions. 

The three executive orders, on the other hand, actually operationalize one subset of actions from each pillar: 

  • One aims to prevent “woke AI” by mandating that the federal government procure only large language models deemed “truth-seeking” and “ideologically neutral” rather than ones allegedly favoring DEI. This action purportedly accelerates AI innovation.
  • A second aims to accelerate construction of AI data centers. A much more industry-friendly version of an order issued under President Biden, it makes available rather extreme policy levers, like effectively waiving a broad swath of environmental protections, providing government grants to the wealthiest companies in the world, and even offering federal land for private data centers.
  • A third promotes and finances the export of US AI technologies and infrastructure, aiming to secure American diplomatic leadership and reduce international dependence on AI systems from adversarial countries.

This flurry of actions made for glitzy press moments, including an hour-long speech from the president and onstage signings. But while the tech industry cheered these announcements (which will swell their coffers), they obscured the fact that the administration is currently decimating the very policies that enabled America to become the world leader in AI in the first place.

To maintain America’s leadership in AI, you have to understand what produced it. Here are four specific long-standing public policies that helped the US achieve this leadership—advantages that the administration is undermining. 

Investing federal funding in R&D 

Generative AI products released recently by American companies, like ChatGPT, were developed with industry-funded research and development. But the R&D that enables today’s AI was actually funded in large part by federal government agencies—like the Defense Department, the National Science Foundation, NASA, and the National Institutes of Health—starting in the 1950s. This includes the first successful AI program in 1956, the first chatbot in 1961, and the first expert systems for doctors in the 1970s, along with breakthroughs in machine learning, neural networks, backpropagation, computer vision, and natural-language processing.

American tax dollars also funded advances in hardware, communications networks, and other technologies underlying AI systems. Public research funding undergirded the development of lithium-ion batteries, micro hard drives, LCD screens, GPS, radio-frequency signal compression, and more in today’s smartphones, along with the chips used in AI data centers, and even the internet itself.

Instead of building on this world-class research history, the Trump administration is slashing R&D funding, firing federal scientists, and squeezing leading research universities. This week’s action plan recommends investing in R&D, but the administration’s actual budget proposes cutting nondefense R&D by 36%. It also proposed actions to better coordinate and guide federal R&D, but coordination won’t yield more funding.

Some say that companies’ R&D investments will make up the difference. However, companies conduct research that benefits their bottom line, not necessarily the national interest. Public investment allows broad scientific inquiry, including basic research that lacks immediate commercial applications but sometimes ends up opening massive markets years or decades later. That’s what happened with today’s AI industry.

Supporting immigration and immigrants

Beyond public R&D investment, America has long attracted the world’s best researchers and innovators.

Today’s generative AI is based on the transformer model (the T in ChatGPT), first described by a team at Google in 2017. Six of the eight researchers on that team were born outside the US, and the other two are children of immigrants. 

This isn’t an exception. Immigrants have been central to American leadership in AI. Of the 42 American companies included in the 2025 Forbes ranking of the 50 top AI startups, 60% have at least one immigrant cofounder, according to an analysis by the Institute for Progress. Immigrants also cofounded or head the companies at the center of the AI ecosystem: OpenAI, Anthropic, Google, Microsoft, Nvidia, Intel, and AMD.

“Brain drain” is a term that was first coined to describe scientists’ leaving other countries for the US after World War II—to the Americans’ benefit. Sadly, the trend has begun reversing this year. Recent studies suggest that the US is already losing its AI talent edge through the administration’s anti-immigration actions (including actions taken against AI researchers) and cuts to R&D funding.

Banning noncompetes

Attracting talented minds is only half the equation; giving them freedom to innovate is just as crucial.

Silicon Valley got its name because of mid-20th–century companies that made semiconductors from silicon, starting with the founding of Shockley Semiconductor in 1955. Two years later, a group of employees, the “Traitorous Eight,” quit to launch a competitor, Fairchild Semiconductor. By the end of the 1960s, successive groups of former Fairchild employees had left to start Intel, AMD, and others collectively dubbed the “Fairchildren.” 

Software and internet companies eventually followed, again founded by people who had worked for their predecessors. In the 1990s, former Yahoo employees founded WhatsApp, Slack, and Cloudera; the “PayPal Mafia” created LinkedIn, YouTube, and fintech firms like Affirm. Former Google employees have launched more than 1,200 companies, including Instagram and Foursquare.

AI is no different. OpenAI has founders that worked at other tech companies and alumni who have gone on to launch over a dozen AI startups, including notable ones like Anthropic and Perplexity.

This labor fluidity and the innovation it has created were possible in large part, according to many historians, because California’s 1872 constitution has been interpreted to prohibit noncompete agreements in employment contracts—a statewide protection the state originally shared only with North Dakota and Oklahoma. These agreements bind one in five American workers.

Last year, the Federal Trade Commission under President Biden moved to ban noncompetes nationwide, but a Trump-appointed federal judge has halted the action. The current FTC has signaled limited support for the ban and may be comfortable dropping it. If noncompetes persist, American AI innovation, especially outside California, will be limited.

Pursuing antitrust actions

One of this week’s announcements requires the review of FTC investigations and settlements that “burden AI innovation.” During the last administration the agency was reportedly investigating Microsoft’s AI actions, and several big tech companies have settlements that their lawyers surely see as burdensome, meaning this one action could thwart recent progress in antitrust policy. That’s an issue because, in addition to the labor fluidity achieved by banning noncompetes, antitrust policy has also acted as a key lubricant to the gears of Silicon Valley innovation. 

Major antitrust cases in the second half of the 1900s, against AT&T, IBM, and Microsoft, allowed innovation and a flourishing market for semiconductors, software, and internet companies, as the antitrust scholar Giovanna Massarotto has described.

William Shockley was able to start the first semiconductor company in Silicon Valley only because AT&T had been forced to license its patent on the transistor as part of a consent decree resolving a DOJ antitrust lawsuit against the company in the 1950s. 

The early software market then took off because in the late 1960s, IBM unbundled its software and hardware offerings as a response to antitrust pressure from the federal government. As Massarotto explains, the 1950s AT&T consent decree also aided the flourishing of open-source software, which plays a major role in today’s technology ecosystem, including the operating systems for mobile phones and cloud computing servers.

Meanwhile, many attribute the success of early 2000s internet companies like Google to the competitive breathing room created by the federal government’s antitrust lawsuit against Microsoft in the 1990s. 

Over and over, antitrust actions targeting the dominant actors of one era enabled the formation of the next. And today, big tech is stifling the AI market. While antitrust advocates were rightly optimistic about this administration’s posture given key appointments early on, this week’s announcements should dampen that excitement. 

I don’t want to lose focus on where things are: We should want a future in which lives are improved by the positive uses of AI. 

But if America wants to continue leading the world in this technology, we must invest in what made us leaders in the first place: bold public research, open doors for global talent, and fair competition. 

Prioritizing short-term industry profits over these bedrock principles won’t just put our technological future at risk—it will jeopardize America’s role as the world’s innovation superpower. 

Asad Ramzanali is the director of artificial intelligence and technology policy at the Vanderbilt Policy Accelerator. He previously served as the chief of staff and deputy director of strategy of the White House Office of Science and Technology Policy under President Biden.

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