Week In Review: AI Was on the Ballot. It Got Crushed.

AI Money Floods the Midterms. Here's What's at Stake Tuesday

Regulation & Policy AI Business & Money Anthropic OpenAI

Tuesday's midterms will help decide how Washington treats AI, and tech money is pouring in. Corporations have spent a record $737 million on these midterms, Public Citizen calculates, with crypto, AI and online-betting firms leading the way, Reuters has reported. Elon Musk, who runs the AI company xAI, is the biggest known donor of the cycle, with more than $276 million to Republican groups, CNBC reports. Not all of it is about AI.

The AI industry has been quieter than its war chest. Its main super PAC network, Leading the Future, funded by investors Marc Andreessen and Ben Horowitz and OpenAI president Greg Brockman, has spent only about $7.4 million on general-election races, The Intercept reports. NBC News found that ads funded by AI groups mostly avoid talking about AI at all. Safety-minded PACs backed by Anthropic and its CEO Dario Amodei have outspent the industry's PACs on AI-focused campaigning, about $44 million to $28 million, according to a campaign finance tracker from the newsletter Transformer. The biggest fight was in New York, where nearly $30 million poured in over Assemblyman Alex Bores, the architect of a state AI regulation bill. He lost June's Democratic primary. "Great site if you want to see where the money is coming from, and who it is going to, on both sides of this debate," AI writer Andrew Curran posted of the tracker.

What changes after Tuesday? If Democrats win the House, as Axios expects, they've signaled a tougher line on AI companies (D.A.D., October 31), and party leaders have discussed a select committee with subpoena power to investigate them. New laws would face a likely Trump veto. The industry is already repositioning: OpenAI plans a post-election policy blitz, including "speed limits" for the most powerful AI and a push to rebrand data centers as "AI compute campuses," and Meta is strengthening ties with Democrats, Axios reports.

Why it matters: AI companies are spending like any big industry with something to lose in Washington, but they've learned the product itself is a hard sell with voters. The fight is also lab versus lab: Anthropic funds one side, OpenAI's leaders the other. "AI is going to be the issue in 2028," OpenAI policy chief Chris Lehane told Axios.

Sources: Public Citizen · Reuters via Kuwait Times · CNBC · The Intercept · NBC News · Transformer AI Campaign Finance Tracker · Axios · Andrew Curran on X

Anthropic Tells Investors AI May Soon Cross Its Own Threshold for Speeding Up AI Research

AI Safety & Risk AI Business & Money Anthropic

In an updated IPO filing on Monday, Anthropic told investors that AI may soon be dramatically speeding up its own development. Its internal estimates and expectations for future models "indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI,'" the company wrote. That's one of the capability thresholds in its own safety rules, which AI writer Andrew Curran summarized as a year's progress equal to two years at the 2018-2024 pace. Anthropic says no current model has crossed it.

The filing also admits the company may not see the moment coming: in the past it has not identified a significant acceleration until after it happened. Anthropic says it is considering rule changes to require human review and approval of some research decisions as Claude does more of that work, and draws a firm line: "We do not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding, if and when that becomes technically possible." It warns that such safeguards, like the limited release of its Mythos model, could slow it down against competitors that don't adopt them.

Why it matters: For years, AI that helps build better AI was a thought experiment. Now a leading lab is telling investors, in a legal filing where misleading statements carry liability, that it may be close. It's a striking disclosure a week after Anthropic's first filing laid out its risks (D.A.D., October 27), and it lands alongside today's MIT research showing AI can edit other AI's inner workings directly. The open question is whether keeping humans in charge holds up once competitors move faster.

Sources: Anthropic S-1/A (SEC) · Andrew Curran on X · Theo Bearman on X

AI Was a Ballot Issue for the First Time. It Got Crushed.

Regulation & Policy Chips, Data Centers & Energy

For the first time, AI was something Americans voted on, and the industry had a bad night. Where data centers were on the ballot directly, they appeared to lose every time. Of the 26 data center measures with results early Wednesday, all 15 that would ban or limit data centers were passing or leading, and all 11 that would allow or support them were failing, according to a tracker of official county results compiled by AI policy advocate Brad Carson. Most margins topped 70%. The votes stretched from Ohio, which had the most measures, to Illinois, Kansas, Florida, New Jersey and California. In Wilmington, Ohio, about 80% voted down four rezonings of land tied to a planned Amazon Web Services data center campus, the Wilmington News Journal reported. In Joliet, Illinois, 79% said no to approving AI data centers. Results are unofficial, some measures were advisory, and a court has put one ban, in Emporia, Kansas, on hold. "If this was the data center election, it was a really bad night for the industry," Heatmap's Jael Holzman wrote.

Meanwhile, the party that campaigned against the industry swept into power. Democrats won virtually every race considered a tossup — and many that weren't: in both federal chambers, in statehouses, governorships, and local races, from Texas to Kansas, winning seats they hadn't won in generations. Democratic campaigns and allied super PACs spent heavily on attack ads about data centers, Heatmap reports, tying opponents to the industry through their votes, past support for projects or tech stock holdings. Sen. Jon Ossoff, re-elected in Georgia, used his victory speech to contrast tech billionaires building bunkers with their own warnings that AI could wipe out humanity, his campaign's transcript shows. Texas showed how far the issue reached. Democrat Gina Hinojosa unseated Gov. Greg Abbott after campaigning against data centers, calling for a moratorium on new ones and an end to industry tax breaks. "Elon Musk moving to Texas to get away from Dems, becoming the biggest partisan megadonor in history, then spending around a half-billion dollars to have his own state go blue immediately in the next election — with data centers the top gov issue — is pretty impressive," NBC News' Benjy Sarlin posted on X.

How much did it matter nationally? In the NBC News exit poll, 23% of voters called AI and data centers crucial to their vote for Congress, and they backed Democrats 66% to 31%. Voters for whom it mattered less split almost evenly, 49% to 48%. But among the issues NBC asked about, AI and data centers ranked lowest in importance, a point tech-industry ally Adam Kovacevich stressed on X. Many voters saw the election mainly as a rebuke of President Trump, NBC's poll found. Stock futures fell overnight as the results came in, with fears about AI and data centers weighing on tech, market coverage reported.

What will Democrats do with the power? They may or may not be able to cobble together a majority to pass AI legislation in Washington. They will certainly pass all sorts of bills at the state and local level. That will affect the AI infrastructure buildout and AI guardrails in ways no one can yet foresee. And then there's oversight. Party leaders have discussed creating a House select committee on AI with subpoena power, an idea Reps. Ted Lieu and Bill Foster pitched to Hakeem Jeffries, who is now in line to become speaker, Nextgov reported. Rep. Greg Casar, who leads the Progressive Caucus, wants to bring in AI CEOs and question them about the risks, Politico reported. "AI will be the number one issue in 2028. And anyone looking to OpenAI's lobbyist for advice will lose," he posted on X the day before the vote, after Politico reported that OpenAI's top lobbyist, Chris Lehane, was pitching 2028 hopefuls on how to talk about AI.

Watch who holds the gavels. Rep. Frank Pallone, in line to chair Energy and Commerce, would oversee most tech, kids-safety and energy bills. He has opposed a separate AI committee. Rep. Jamie Raskin would run Judiciary, where Democrats sided with The New York Times last week in its copyright fight with OpenAI. In the Senate, Maria Cantwell, who led the 2025 fight that stopped a ban on state AI laws, is in line to chair the Commerce Committee.

Democrats have signaled four priorities: - Let states keep regulating AI. The Republican push for a single federal rule overriding state AI laws now looks dead. Democrats ran ads against four Republicans who had voted to block state rules, Axios reported. - Electricity bills. Jeffries has said protecting consumers from rising power costs tied to data centers would be a priority. - Kids and chatbots. Bills to restrict AI companions for minors already have support from both parties. - No bailouts. Casar and Rep. Maxine Waters want a House vote declaring that failing AI companies should go bankrupt, not be rescued.

The party isn't united. Progressives including Casar and Sen. Bernie Sanders back a ban on superintelligent AI; Jeffries hasn't endorsed it. Critics say the leaders of Jeffries' own AI commission are too close to Big Tech. The industry was ready for this: OpenAI planned a post-election policy push, and Meta has been courting Democrats, Axios reported.

Why it matters: The AI industry spent heavily, kept quiet about AI in its ads, and now faces a Congress controlled by the party that made data centers and power bills a campaign issue. Expect hearings before laws: executives under oath, documents subpoenaed, and close looks at AI companies' ties to the Trump administration, starting in January. States are likely to keep writing their own AI rules. And the exit poll gives both sides a talking point. AI is not yet a top issue for most voters, but for the quarter who say it is, it pointed one way.

Sources: NBC News (results) · NBC News (exit poll) · CBS News · The Washington Post · CNBC · Nextgov · Politico · Axios (ads) · Axios (OpenAI) · Wilmington News Journal · Ballotpedia · Heatmap · Ossoff campaign · ABC News (Texas) · Benjy Sarlin on X · Greg Casar on X · Adam Kovacevich on X

Google Lets Schools Turn Off Its AI. The Price: Losing Google Search.

Education Kids, Teens & Mental Health Google

Parents and teachers asked Google for a way to keep its AI away from kids. Google said yes, with a catch. Starting early next year, it will turn off AI tools in its software for K-12 students unless school administrators choose to switch them on, The New York Times reports. But schools that restrict AI entirely will also lose Google search. "Search and A.I. are deeply integrated," said Chris Phillips, Google's vice president for education. If a school has banned AI, he said, students "will not have access to search, and they'll see a message from their school that indicates it's not available."

Schools that allow AI will get two choices for search: the regular version, with AI Overviews and AI chat, or one run through Guided Learning, a student version of Google's Gemini chatbot meant to walk students through a topic rather than hand them answers. Google already offers a links-only "Web" view of its search results, but neither option it's giving schools works that way. Google is also reversing an August change that switched on AI features by default in its Classroom app, which upset some school leaders.

The stakes are high because Google's Gmail, Docs and Classroom apps are everywhere in K-12 schools. And the pushback was already building. In September, New York City and Los Angeles, the nation's two largest school districts and both Google customers, broadly restricted student access to generative AI on school devices. Los Angeles officials had hoped students could keep searching with AI Overviews turned off. A University of Southern California education professor told the Times the move could further energize the anti-tech movement among parents and educators: "This is a particularly clear example of the tech industry going out of its way to force A.I. on us all — even if we have said we don't want it."

Lina Khan, who led the Federal Trade Commission under President Biden, went further. "Google is using its search monopoly to coerce schools into adopting AI," she wrote on X. "This highlights the danger of allowing an unregulated monopolist to control an essential service." Not everyone agrees. "This article is getting posted everywhere this morning, but this decision is being incorrectly framed as punitive," AI writer Andrew Curran posted. "The old Google search is gone."

Why it matters: Google says the reason is technical: AI is now built into search. The business logic points the same way. Google is betting its future on AI search, and running a separate, AI-free version for schools would cut against that bet. Today's students are also tomorrow's users. But the move hands critics a vivid example of a dominant company pushing AI on children, just as lawmakers are acting: New York passed a law last week barring a range of AI features for minors. Kids and screens is one of the few tech issues with support in both parties. Khan's reaction shows where the fight is headed: critics will frame it as a monopoly problem, not just a schools problem. Whoever controls Congress after the midterms, expect it to come up in hearings and state bills.

Sources: The New York Times · TechCrunch · Chalkbeat · Forbes · Lina Khan on X · Andrew Curran on X

How Hackers Stole $6.3 Billion From Binance: A Fake Job Interview, a Booby-Trapped AI Download and Binance's Own AI Tool

Cybersecurity Finance & Banking

When we first covered the biggest crypto heist ever, nothing reported said AI played a role (D.A.D., October 30). Binance's own account, released Tuesday, says it did. The FBI has blamed North Korea for the theft of about $6.3 billion, NPR and NBC News report. North Korea denies it, CNBC reports.

Binance's report describes a months-long campaign. In June, an engineer on its wallet team searched online for a popular AI coding tool and downloaded a tampered installer. Binance caught it and replaced his laptop, but the attackers had learned who worked on the wallets. In September, a second engineer got a job approach through a legitimate hiring site. A fake recruiter interviewed him on live video, sharing personal photos and videos on social media to build trust. In a second interview, he was told to download an "assignment" onto his work computer. It carried malware Binance's security tools didn't catch. On October 20, the attackers used that computer and an internal Binance AI tool to take over two more engineers' machines, one holding a key credential. Nine days later, they used it to make Binance's wallet system sign away billions.

Stopping it was hard. Withdrawals were suspended, but the attackers had planted permissions on the blockchain itself that kept money moving. The last transfer went through nearly four hours after the first. Binance says about $2.85 billion has been frozen, it will cover all losses, and it has already replaced 98% of the stolen tokens. It also says it blocked 57 other suspected North Korean attacks this year.

"Tremendous public service from Binance to publish this," Haseeb Qureshi, managing partner at the crypto investment firm Dragonfly, wrote on X. "The Internet is now going to be full of AI-accelerated social engineering toxic sludge, and it's your job to be hypervigilant."

Why it matters: Two lessons reach well beyond crypto. First, AI tools are now a way in: workers hunting for the latest AI app can download a fake, and an in-house AI assistant with wide access can be turned against its owner. Second, the weak points were people: an engineer installing software, and another looking for a job. Qureshi's advice applies to any organization that runs on laptops: assume you'll be breached, watch around the clock, and know how to shut everything down before you need to.

Sources: Binance (on X) · NPR · NBC News · CNBC · Haseeb Qureshi on X

New Governors Could Pause 41% of America's Planned Data Centers, Tracker Finds

Chips, Data Centers & Energy Regulation & Policy

The AI boom runs on data centers, and on Tuesday voters turned against them, from county ballots to governor's mansions. Data centers are warehouse-size buildings packed with the chips that train AI models and answer every chatbot request. The industry says it needs far more, because every new user and every AI agent running a long task takes more computing. Gartner expects data centers' electricity use worldwide to grow 26% this year alone.

Much of that planned growth now sits in hostile territory. States where the new governor backs a pause hold 159 gigawatts of planned data centers, 41% of the national pipeline, according to Cleanview, a research firm whose project tracker has been used in grid studies. Another 18% is in states whose winners want new rules but no pause. Locally, every data center ballot measure with results went against the industry (D.A.D., November 4).

The biggest prize is Texas, where Democrat Gina Hinojosa, who called for a moratorium, unseated Gov. Greg Abbott. Georgia elected Keisha Lance Bottoms, who wants a statewide pause; New York re-elected Gov. Kathy Hochul, who proposed one in July. AI data center stocks and SpaceX fell on the Texas result, CNBC reported.

In Texas, the brakes are already on. Abbott paused new data center permits and grid approvals by directive starting in August, pending a grid and water audit, and Hinojosa can simply leave that pause in place, the Texas Tribune notes. She has said her pause would cover new permits while lawmakers write protections, not projects already under construction, KTAB reported. Several trackers put Texas construction at roughly 20 gigawatts. Her plan sets conditions, not a ban, as tech writer Tae Kim noted: union labor, no subsidies, and proof that households won't pay more for power or water. Those need the Legislature, which convenes Jan. 12 with Republicans still holding the state Senate. Governors also control air permits for the gas plants many data centers build on site, Cleanview founder Michael Thomas noted.

In Washington, the likeliest law is about power bills. The House passed a bill 417-3 in September nudging states to make big data centers pay their full electricity costs; a Senate Democrat blocked it as too weak, and Trump got tech giants to sign a voluntary pledge to the same end in March. Bipartisan bills to keep AI companion chatbots from minors are another candidate. Broader bipartisan safety talks in the Senate have stalled. Some Democrats want far more. "Top of the Democratic agenda on day 1 needs to be a pause on advanced AI development, regulation of this out of control industry, and a ban on artificial superintelligence," Rep. Yassamin Ansari posted on X.

"Tuesday's results don't signal the end of the data center boom," Thomas wrote, though he expects pauses in some of the biggest markets and new rules nationwide, even in Texas.

Why it matters: Data centers need land, power and permits now, and local voters, governors and regulators control those. A slowdown in states holding two-fifths of planned capacity would ripple through AI companies' spending plans and push building toward friendlier states. If Congress acts, the best bet is on who pays for data centers' power: both parties and the White House are already on record.

Sources: Cleanview · Michael Thomas on X · Texas Tribune · KTAB/KRBC · Gartner · CNBC (stocks) · CBS Texas · Fox 7 Austin · TCEQ · Axios (House vote) · CNBC (Senate) · Inside Climate News (pledge) · Miller-Meeks (chatbot bill) · The Next Web, citing Reuters (Senate talks) · Tae Kim on X

Outside Review Finds AI Is Now Roughly Doubling the Pace of AI Progress at Anthropic

AI Safety & Risk Anthropic

The question that worries AI safety researchers most is whether AI has started speeding up its own development. An independent evaluator with inside access now says yes, probably, at least at one lab. From Aug. 12 to Oct. 29, staff from METR, a nonprofit that tests AI systems, reviewed what it calls unprecedented internal data from Anthropic, from training metrics to staff interviews. METR took no payment. Its conclusions:

• Faster progress. As of October, Anthropic's models are likely improving on well-defined tasks about twice as fast as they did from March 2024 to October 2025: roughly two years of progress in one. METR says it is highly uncertain and would not be surprised by anything from 1.3 to 3 times.
• AI is probably the cause. METR's best guess is that about 80% of today's speedup comes from Anthropic using AI to do its research. It is confident the cause is not faster growth in computing power, but Anthropic's own staff don't agree on the rest. For now AI mostly assists researchers rather than working alone, though researchers described early signs of fully autonomous contributions.
• No brakes in sight. METR found no clear bottlenecks for the next 12 months, so progress could speed up further, though it says it may have missed some.

Much of the evidence is hidden. Anthropic had the right to redact confidential material from METR's roughly 100-page report, and cut most of the evidence METR found most informative, tightening its redactions in the final days. Anthropic said the cuts were meant to keep information from helping rival AI developers. "As a consequence, the public has to rely on METR's judgment much more than would be ideal, given the weight of the questions answered here," the report says.

Some forecasters were caught off guard. METR researcher Ryan Greenblatt wrote that he had been seriously wrong: he expected AI to speed up its own development far less this year. His rough math suggests AI is speeding up Anthropic's software research about 4.5 times, a pace the influential "AI 2027" forecast didn't expect until around March 2027. He says the report makes superintelligent AI within one to two years significantly more likely.

Why it matters: Anthropic told investors on Monday it may soon cross its own threshold for AI-driven research acceleration (D.A.D., November 3). An outside reviewer now says the speedup is already under way. If AI is helping build better AI, the timelines for job disruption, safety rules and everything else shrink, just as the public turns against the industry. The caveat is real: the strongest evidence is locked away, and the company being reviewed decided what stayed secret.

Sources: METR · Ryan Greenblatt on X

OpenAI's Answer to the Data Center Backlash: No NDAs, Public Water Data and a New Name

Chips, Data Centers & Energy Regulation & Policy OpenAI

Days after voters rejected data centers across the country, OpenAI is trying to win them back. The company published a National Community Compact, a set of promises for every campus it owns and operates, and a policy blueprint asking lawmakers to turn similar rules into law for the whole industry. The documents also adopt a new name: data centers are now "compute campuses," a rebrand Axios had reported would be part of OpenAI's post-election policy push.

The promises read like a list of the backlash's complaints. OpenAI says it will pay the full cost of the electricity and grid upgrades its campuses need, and put up money in advance so other customers aren't stuck with the bill if a project stalls. It will publish each site's water and electricity use, construction plans and independent noise studies, and report annually on hiring. It will stop asking public officials to sign nondisclosure agreements, except for narrow security and trade-secret protections; it voided the ones in Effingham County, Georgia, in July. Several of these echo demands from critics such as Texas Gov.-elect Gina Hinojosa, who campaigned on banning data center NDAs and making companies prove households won't pay more.

The blueprint asks lawmakers to require those disclosures, bar NDAs with officials, force big power users to cover their grid costs, and publish the terms of tax breaks, with clawbacks if companies fall short. It also asks for faster permitting and grid connections, and restored clean-energy tax credits, and argues against blanket rules requiring data centers to build their own power plants. OpenAI acknowledges the mood. "Americans are understandably highly skeptical that big investments by Silicon Valley-based companies will deliver tangible benefits to their hometowns," the blueprint says.

The industry's campaign money didn't stop the backlash either. Its main super PAC, Leading the Future, spent $4.8 million on Republican Darline Graham's South Carolina Senate race; she lost to Democrat Annie Andrews, who called her "Data Center Darline." The PAC put no money into fighting the roughly 40 data center ballot measures that passed, Semafor reported, and was caught off guard by their success, one Republican operative said. The timing was not lost on observers. "OpenAI kicked off its big charm offensive this morning after data center moratoriums went 43-1 during the midterms," AI writer Andrew Curran posted.

Why it matters: The industry's fight has moved to the places where data centers get built, and OpenAI is trying to set the terms before states and towns set them for it. Some of the pledges are real concessions; others are an argument for faster permits and fewer power mandates. The compact covers only campuses OpenAI owns and operates, and much of it is promises to disclose. Whether communities accept a deal now, after voting no, is the test.

Sources: OpenAI · National Community Compact (PDF) · Compute Campus Policy Blueprint (PDF) · Axios · Andrew Curran on X

Democrats Weigh a Corporate Crackdown. Lina Khan Says Start With AI.

Regulation & Policy AI Business & Money

While OpenAI courts communities, some Democrats want to put executives under oath. Senior congressional Democrats have been studying a 181-page plan, drafted by the progressive think tank Groundwork Collaborative, naming hundreds of executives and companies to investigate once the party takes Congress in January, the Washington Sun reported. Its targets include the biggest tech companies, AI labs, natural gas firms, private prisons and nursing home operators. One proposed hearing would press online sports-betting CEOs on how they use AI to encourage compulsive gambling. "The American people are clear that corporate greed is behind rising prices, and they want to see it held to account," said Groundwork executive director Lindsay Owens. "We're talking resignations of major CEOs, hauling people in, material restitution."

Party leaders are cooler. "We all get a lot of emails," a Democratic aide told Semafor. "It's one of many." Rep. Jamie Raskin, the incoming House Judiciary chair, told Semafor he hadn't seen the plan: "We're not taking people or corporations that we want to pursue in a vendetta-like fashion: That's Donald Trump land." Centrists warn that a broad assault on business could cost Democrats the edge on the economy they just won.

Lina Khan, who chaired the Federal Trade Commission under President Biden, made the case for investigating, and for putting AI near the top. "AI markets should be high on the list of investigations," she wrote on X. "The business decisions of the major AI firms have huge public ramifications, yet the public is at a severe informational disadvantage when it comes to how these markets work and the choices these firms are making." As a House Judiciary staffer, Khan worked on the 2019–2020 investigation of Amazon, Apple, Facebook and Google, which she says laid the groundwork for later lawsuits and proposed laws. Her advice to the new majority: let subcommittee chairs issue their own subpoenas, spend months preparing before CEOs testify, and rebuild Congress's depleted research staff.

Why it matters: Oversight is the one power a Democratic Congress holds without needing President Trump's signature, and as Khan argues, investigations are often how laws get written: subpoenaed documents become evidence for bills and lawsuits. Sen. Elizabeth Warren, likely to chair the Banking Committee, is already warning Big Tech CEOs to expect grilling, Semafor reports. AI companies, which courted the administration and spent heavily in the midterms, are an obvious target. The fight is over how wide to swing.

Sources: The Washington Sun · Semafor · Lina Khan on X

Congress Summons Nvidia's Huang After Reports Chinese Spy Agency Targeted Him

China & Geopolitics Chips, Data Centers & Energy Nvidia

The story of the suspected Chinese spy close to Nvidia's CEO got more serious this week. Alice Huang, an executive at the Singapore data-center company Megaspeed, was recruited by China's Ministry of State Security, Beijing's top spy agency, to gather intelligence on Jensen Huang and potentially influence Nvidia to push for its most advanced chips to be sold to China, The New York Times reported, citing people briefed on a memo that circulated among top Trump administration policymakers last spring. The memo said the two were romantically involved, the Financial Times reported, going beyond the close relationship the Times first described (D.A.D., October 30). It was shared with a small group of top officials shortly before President Trump traveled to Beijing for a summit with Xi Jinping, the FT reported. Megaspeed builds data centers in Southeast Asia and rents their computing power to the Chinese internet giant Alibaba, the Times reports, giving China a back door to advanced Nvidia chips it cannot buy directly.

Congress is now asking questions. The Republican chairs of the House committees on China, foreign affairs and intelligence, Reps. John Moolenaar, Brian Mast and Rick Crawford, asked Huang to a joint closed-door briefing on Nov. 18, the FT reported. "It is vital that Congress determines the extent to which US national security has been placed at risk," they wrote. Nvidia would not say whether Huang will appear. Singapore police say they are investigating Megaspeed over suspected breaches of local law. Nvidia declined to comment on the memo or the reported relationship; it has previously said Huang meets thousands of customer executives a year and that allegations of chip diversion through Megaspeed were investigated and debunked. The White House and CIA declined to comment. China calls the reports a smear. Alice Huang and Megaspeed have not commented.

Critics say the Commerce Department has some explaining to do. "What is a POSSIBLE good explanation for why Megaspeed is still receiving chips? Why is there not a license requirement for AI chip shipments to all of Southeast Asia?" wrote Chris McGuire, a senior fellow for China and emerging technologies at the Council on Foreign Relations who previously worked at the National Security Council and the State Department. He argues that the agency, though presumably briefed by intelligence officials, has not tightened rules on Megaspeed or the region, which has become one of the world's biggest importers of AI chips.

Why it matters: Huang is the most influential voice in Washington's fight over how many AI chips to sell to China, and he has won much of it: the administration has loosened limits and taken a cut of some sales. If Beijing's spy service targeted him to shape U.S. chip policy, as the intelligence reportedly suggests, every argument Nvidia has made against export controls will now be read in that light, and lawmakers of both parties will want to know why the administration acted on so little of it. None of the intelligence claims have been made public, and Huang has not been accused of wrongdoing.

Sources: The New York Times · Financial Times · Financial Times (Congress) · CNBC · The New York Times (Oct. 29) · ABC News (Nvidia response) · Chris McGuire on X

AI May Not Kill Your Job. It Could Make It Less Valuable, Economists Argue

AI & Jobs

The usual fear about AI and work is automation: machines take the job. Three economists propose a different worry: commoditization. When technology makes a job easier, anyone can do it, so workers become interchangeable and employers stop competing for them. "Automation implies job apocalypse. Commoditization implies plentiful jobs with low wages," UC Berkeley economist Jón Steinsson wrote on X.

In a working paper, Steinsson, his Berkeley colleague Emi Nakamura and Masao Fukui of Boston University model what happens when firms standardize tasks so that output depends on their systems rather than on a worker's know-how. Productivity rises and jobs get easier to fill, but workers lose bargaining power, and their share of what they produce falls, especially at the biggest firms. The authors say the model helps explain why pay in retail and other service jobs has lagged productivity, and why big firms' traditional wage premium has shrunk. They find that hiring costs per worker at firms with more than 5,000 employees are roughly a third of those at firms with fewer than 100.

The paper itself is about past technology, from Adam Smith's pin factory to warehouse workers following handheld devices. Applying it to AI is Steinsson's own extension: AI will automate some jobs, he wrote, but in many cases it will make technical work easier without eliminating it, the way "vibe coding" with AI is easier than real coding, so many more people can do it. "Perhaps in the 21st century various white-collar jobs will be commoditized (as opposed to fully automated)," he wrote. Jason Furman, a Harvard economist who chaired President Obama's Council of Economic Advisers, called the idea intriguing.

Why it matters: Most AI-and-jobs debate asks how many jobs will disappear. This asks what happens to the ones that remain. If AI lets a junior employee do what used to take years of expertise, the expert's leverage shrinks even if nobody is laid off. That's a quieter risk, and a harder one for policy to address than mass unemployment: the paycheck problem, not the pink slip.

Sources: Fukui, Nakamura and Steinsson (PDF)

Assignment Design, Not Access, Drives Better AI Use in Classrooms

Education

What happens when students are allowed to use AI on their essays? A three-year study at New Zealand's University of Auckland, drawing on 1,894 survey responses from a large first-year computer science course, found the answer depends less on the tool than on how the assignment is built. When AI was simply permitted for short ethics essays in 2024 and 2025, about two-thirds of students used it. In 2026 the instructors made AI an expected part of a structured process: write a complete draft first, with a checklist requiring at least two stakeholders, a counterargument and flagged claims needing evidence; then ask an AI tool to refine, not rewrite, accepting or rejecting each suggestion; then submit a short reflection on what changed, plus a disclosure form. Skipping the draft or the form meant a zero. Use rose above 90%.

Students mostly used AI to polish grammar and style, not to think for them; using it for brainstorming fell from 47% to 15%. Graders judged that about four in five submissions showed critical engagement with the AI's suggestions, and the share of essays where they rated the AI's effect as positive rose from 47% to 66% between the two essays. Students explained their rejections in their own words: "It told me one of my sources was wrong. It wasn't. It just hallucinated." But AI use made no measurable difference to grades once students' earlier writing ability was taken into account. ChatGPT's share of student use fell from about 90% to about 60% as Claude, Gemini and Grammarly gained ground.

Why it matters: For schools and employers debating whether to ban or embrace AI, this points to a third option: design the work so people do the thinking first and use AI to check and polish. It changed how students used the tools more than it changed their grades. The authors caution that it's one course at one university, relies partly on self-reports, and that the jump in use came alongside a policy that expected it.

Source: arxiv.org

AI Tools Shape News Drafts Before Editors Ever See Them

A new study based on interviews with 16 journalists at public, commercial, and state-affiliated news organizations finds that generative AI tools are quietly making editorial judgment calls—like which angles or framings to generate across multiple story drafts—before human editors ever see the final product. Researchers say these AI-shaped choices affect news diversity but happen inside a black box: editors sign off on finished stories without visibility into which alternatives the AI generated, favored, or suppressed along the way.

Why it matters: Newsrooms are accountable for what AI tools produce but increasingly can't see how those tools arrived there, raising hard questions about who's really responsible when AI quietly narrows the range of stories readers see.