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.”

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now When models attempt to get their way or become overly accommodating to the user, it can mean trouble for enterprises. Therefore, it’s essential that, in addition to performance evaluations, organizations conduct alignment testing. However, alignment audits often present two major challenges: scalability and validation. Alignment testing takes so much time for human researchers, and it’s challenging to be assured that the audit caught everything.  In a paper, Anthropic researchers said they developed auditing agents that achieved “impressive performance at auditing tasks, while also shedding light on their limitations.” The researchers said these agents, which were created during the pre-deployment testing of Claude Opus 4, improved alignment validation tests and allowed researchers to run multiple parallel audits at scale. Anthropic also released a replication of its audit agents on GitHub.  New Anthropic research: Building and evaluating alignment auditing agents. We developed three AI agents to autonomously complete alignment auditing tasks. In testing, our agents successfully uncovered hidden goals, built safety evaluations, and surfaced concerning behaviors. pic.twitter.com/HMQhMaA4v0 — Anthropic (@AnthropicAI) July 24, 2025 “We introduce three agents that autonomously complete alignment auditing tasks. We also introduce three environments that formalize alignment auditing workflows as auditing games, and use them to evaluate our agents,” the researcher said in the paper.  The AI Impact Series Returns to San Francisco – August 5 The next phase of AI is here – are you ready? Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation. Secure your spot now – space is limited: https://bit.ly/3GuuPLF The three agents they explored were: Tool-using investigator agent for

Even generative AI critics and detractors have to admit the technology is great for something: transcription.If you’ve joined a meeting on Zoom, Microsoft Teams, Google Meet or other video call platform of your choice at any point in the last year or so, you’ve likely noticed an increased number of AI notetakers joining the conference call as well.Indeed, not only do these platforms all have AI transcription features built in, but there are of course other stand alone services like Otter AI (used by VentureBeat along with the Google Workspace suite of Apps), and models such as OpenAI’s new gpt-4o-transcribe and older open-source Whisper, aiOla, and many others with specific niches and roles.One such startup is San Fransisco-based Freed AI, co-founded in 2022 by former Facebook engineers Erez Druk and Andrey Bannikov, now its CEO and CTO, respectively. The idea was simple: give doctors and medical professionals a way to automatically transcribe their conversations with patients, capture accurate health specific terminology, and extract insights and action plans from the conversations without the physician having to lift a finger.

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.

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.”

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What role should oil and gas companies play in climate tech? —Casey Crownhart After writing about Quaise, a geothermal startup that’s trying to commercialize new drilling technology, I’ve been thinking about the role oil and gas companies are playing in the energy transition. It’s becoming increasingly common in climate tech to see a startup join up with a bigger fossil fuel company in its field, like Quaise has with Nabors Industries, one of the biggest drilling firms in the world.
This industry has resources and energy expertise—but also a vested interest in fossil fuels. Can it really be part of addressing climate change? Read the full story. This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.
Google DeepMind’s new AI can help historians understand ancient Latin inscriptions Google DeepMind has unveiled new artificial intelligence software that could help historians recover the meaning and context behind ancient Latin engravings. Aeneas can analyze words written in long-weathered stone to say when and where they were originally inscribed.  It follows Google’s previous archaeological tool Ithaca, which also used deep learning to reconstruct and contextualize ancient text, in its case Greek. But while Ithaca and Aeneas use some similar systems, Aeneas also promises to give researchers jumping-off points for further analysis. Read the full story. —Peter Hall The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Donald Trump has unveiled his AI Action Plan He signed multiple orders to boost US AI exports and loosen regulations. (Bloomberg $)+ The plans could reshape how US tech firms train their models. (TechCrunch)+ We’re living in the age of chatbot culture wars. (NYT $)2 China hopes to sell its excess computing powerAfter rapidly building too many data centers. (Reuters)+ China built hundreds of AI data centers to catch the AI boom. Now many stand unused. (MIT Technology Review) 3 How corn is worsening Indiana’s dangerous heatwaveResidents are increasingly at risk of severe heat illness, as the moisture from corn increases humidity levels. (Axios)+ What is corn sweat, exactly? (Vox)+ Here’s how much heat your body can take. (MIT Technology Review)4 What’s next for Tesla?Its sales are falling, and its push into robotaxis is coming at a steep cost. (TechCrunch)+ Elon Musk appeared oddly upbeat on an analyst call. (The Information $)+ Why scaling up robotaxi fleets is such a challenge. (FT $)5 The US is poised to reinstate a banned herbicideDicamba has caused substantial damage to neighboring crops in the past. (WP $)+ The weeds are winning. (MIT Technology Review) 6 Why Amazon is eyeing AI gadgetsA bracelet that records conversations is the latest addition to its roster. (WSJ $)+ Why AI hardware needs to be open. (MIT Technology Review)7 Americans love China’s short video dramasWatch out Hollywood—duanju clips are on the rise. (Wired $) + China’s next cultural export could be TikTok-style short soap operas. (MIT Technology Review) 8 How a YouTube channel captured the spirit of rogue music discoveryMusic Place has gained a cult following from sharing obscure gems. (Pitchfork) 9 Pinterest isn’t immune to AI slopGood luck remodelling your home based on its fantastical designs. (FT $) 10 AI videos are coming to YouTube ShortsIt’ll do everything from creating backgrounds to conjuring up video elements from a text prompt. (Ars Technica)+ What’s next for generative video. (MIT Technology Review)
Quote of the day “You could throw out the results of all these papers.”
—Jeffrey Morris, a biostatistics professor at the University of Pennsylvania, criticizes scientific papers co-authored by the US government’s vaccine safety investigator and vaccine skeptic David Geier to the Atlantic. One more thing What is AI?Artificial intelligence is the hottest technology of our time. But what is it? It sounds like a stupid question, but it’s one that’s never been more urgent.If you’re willing to buckle up and come for a ride, I can tell you why nobody really knows, why everybody seems to disagree, and why you’re right to care about it. Read the full story. —Will Douglas Heaven We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)+ What could be more fun than bumping into Billy Joel while cycling a pedicab around NYC.+ Margarita ice cream is certainly one way to cool down in the summer heat.+ The Denver Museum of Nature & Science has made an extremely unusual discovery—a 67.5 million year old dinosaur fossil under its parking lot.+ In praise of Jane Austen, by way of Clueless.