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OpenAI’s chief global affairs officer Chris Lehane thinks the 2028 presidential election could be a defining moment for AI. And he wants politicians to start developing policies that address Americans’ concerns about the technology, rather than simply paying lip service to anti-AI sentiment and thebacklash against data centers. In anew essay, Lehane compares AI’s potential to reshape the economy to President Franklin D. Roosevelt’s New Deal, the 1930s set of federal programs and reforms enacted after industrialization and the Great Depression shattered the old economic order. He observes that Americans today feel similarly anxious about losing control over their economic futures and urges politicians to find a “compelling third path” that allows people to share in AI’s benefits. He lays out five policy priorities, spanning worker protections and education to AI safety and data center development. The essay comes on the heels of a stunning Democratic victory in the midterm elections, in which Democrats flipped control of Congress amid widespread voter frustration over the cost of living. Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, told TechCrunch that Lehane’s rhetoric marks a notable shift fromOpenAI’s policy agenda last year,which focused on accelerating AI development, reducing regulatory barriers, and expanding infrastructure. Unsurprisingly, many of Lehane’s proposals would encourage wider AI adoption and support the infrastructure expansion companies like OpenAI need to grow. The original New Deal established protections for workers and placed constraints on corporate power. It’s less clear how Lehane’s vision would hold AI companies accountable for the economic disruption their technology could create. “Invoking a New Deal metaphor is to invoke state capacity to actually benefit the public,” Brennan said. “This is written by a private company that is trying to advocate for policies for its own benefit. It is ahistorical at best and harmful at worst.” While AI wasn’t a dominant issue in the midterms, opposition to data centers emerged as a major bipartisan concern in several races in the midterms. And Lehane may be right that AI will become a bigger part of the conversation over the next two years. Affordability is already shaping up as a key issue for the 2028 election as Americans grapple with inflation, tariffs, and the rising cost of living. AI could become an increasingly large part of that conversation as voters stress about data centers hiking up electricity bills, AI replacing their jobs, and technology’s economic gains flowing only to a handful of wealthy companies. Lehane acknowledges many of these concerns, but he offers few concrete proposals to prevent AI’s gains from becoming concentrated. Instead, he largely pitches AI as a path to greater prosperity for Americans willing to embrace it. Take his proposals for the tax code. He suggests incentives for workers to learn AI skills, easier capital access for entrepreneurs, and new approaches to employee ownership and profit-sharing. Those are not the same as binding requirements that would ensure workers share in AI-generated wealth or that companies pay the costs of displacing workers. “I was struck by how much of this policy is for a future…that is already predicated on mass AI adoption and AI benefiting society, which we have yet to see,” Brennan said. “All of it is predicated on benefiting from AI’s upside.” Brennan said it would make more sense to see things like a revised corporate tax rate or tax incentives for hiring human beings rather than automating jobs, as well as ways to keep companies from amassing outsize market power. Lehane’s emphasis on expanding AI’s economic opportunities, rather than limiting potential harms, extends to data centers. He notes concerns about data centers while emphasizing the construction jobs and local tax revenue they could generate. He then warns that politicians who support a data center moratorium could jeopardize America’s lead over China, going so far as to compare that stance to the 2002 vote to authorize the Iraq war. Lehane also makes child safety and education central to his proposed agenda, stressing the importance of age-appropriate protections andsafeguards around AI companionsfor minors. He also warns against keepingAI out of classrooms, arguing that doing so could lead to inequality between wealthy students and “children in rural communities.” But the argument takes for granted that AI improves learning, a claim that remains unproven and one critics say deserves more examination than more funding or individualized attention from human teachers. Lehane also calls forenforceable AI safety standards,independent evaluations, public oversight, and the ability to restrict AI systems or use a kill switch to shut them down — thoughrecent studies showthat OpenAI and other AI labs haven’t published comprehensive plans for what they would do if a model escaped human control. Brennan called these stances “disingenuous,” pointing to OpenAI’s history of opposing legislation designed to impose such measures. In 2024, for example, OpenAIopposedCalifornia’s AI safety bill, SB 1047, which would have mandated catastrophic risk evaluations and shutdown capabilities. Last year, OpenAI alsosought to limit state regulation, arguing that states could undermine American innovation. The company has more recently shifted some of those positions, backing several state safety laws and saying it would be open to independentevaluators embeddedin the company. Lehane also argues that people should maintain control over consequential decisions made using AI, rather than handing off judgment entirely to machines.But that raises the question of what human control really looks like in a society where humans are increasingly being required to use AI in education, work, healthcare, and government. Throughout his essay, Lehane frames AI as a technology that could give Americans back their sense of agency and economic opportunity. But he ties average Americans’ “middle class” success to participation in an economy increasingly shaped by companies like OpenAI. Whether his policies will meaningfully redistribute power or subtly entrench it is less clear. TechCrunch reached out to OpenAI for more specifics on Lehane’s proposals and the company’s stances, but it did not respond by the time of publication.
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Very few people are using personal AI agents to order Ubers, apparently. On the transportation giant’sthird-quarter earningscall on Wednesday, the company said that only four rides were ordered through an AI agent during its busiest week in October: the week of Halloween. While more people used an AI agent to order food through its delivery service, Uber Eats, the volume was still fairly small compared to the overall number of trips. Uber’s chief financial officer, Balaji Krishnamurthy,toldWall Street analysts on the call that the company handled around 320 million trips and orders across Uber and Uber Eats during the week of Halloween, but only 500 Uber Eats orders were placed by an AI agent. “It is very, very early and very limited traction that we are seeing so far,” said CEO Dara Khosrowshahi, referring to the low number of orders placed by AI agents. “Listen, we hope that there will be more traction.” The surprisingly low numbers of AI-initiated transactions come amid growing hype for a new wave of AI agents that don’t just answer questions but also handle tasks on users’ behalf. There’s been an explosion of personal AI startups, including one of the buzziest, Instinct, which was founded last year and raised its most recent round of funding at a$10 billion valuation.Meta’s Muse also became the No. 1 app in Apple’s U.S. App Store last month, topping 10 million users,per Meta’s own reporting. The company said many were using it to shop and transact with businesses. OpenAI, Anthropic, Google, and SpaceXAI (Grok) are also now offering their own AI agents, as arenumerous smaller startups. Still, early numbers from public companies indicate the agentic web still has a long way to go. DoorDash, for instance, said last week on its earnings call that it hasonly received a few hundred ordersfrom AI agents so far, as most customers are still placing orders through the DoorDash app. Uber is seeing the same behavior, it seems. Khosrowshahi pointed out that the average time to book a ride is only 50 seconds in the company’s app, and re-ordering a favorite food only takes 90 seconds. That suggests an AI agent isn’t necessarily saving anyone time. Despite the low number of AI-driven transactions, Khosrowshahi seemed bullish on the idea of agents in general. “We think that is another opportunity to reach our platform. We think it will be a net positive in terms of demand on the ecosystem,” he said. Right now, there are around eight major AI assistants on the market, Khosrowshahi noted, and he expects that number to grow to more than 10 in time. “Every single AI system company is talking to us,” he added.

Nothing, the smartphone startup behind the distinctiveNothing Phone, is working on an AI product, but what it is remains unclear. On Wednesday, CEO Carl Peiposted on Xthat the company’s first “AI-native product” ships in December. “It’s a tool, but one built with the personality and care that have come to define a Nothing product. It has no new screen, and it couldn’t have been an app,” Pei wrote. Pei has teased an AI-first devicefor some timeand the companyhas also saidthat it plans to release a pair of AI-linked smart glasses, as well as earbuds with AI integrations. Pei’s description adds up to a screenless non-app that uses AI? He also calls it a “productivity tool.” Adding further mystique to the announcement, Pei seems to downplay any link to AI wearables. “The whole industry is hunting for its iPhone moment: the pendant, the pin, the glasses, the companion, some magical consumer device that makes AI part of everyone’s life,” Pei wrote. “I admire the boldness, but I read this moment differently.” No firm release date has been announced, but Nothing fans should know soon enough what the company has in store for them.
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Political groups both supporting and opposing the AI industry spent millions of dollars trying to influence Tuesday’s midterm elections and shape the future of AI regulation. That spending produced mixed results, with some of the most heavily backed candidates losing their races. On the industry side, two AI-focused political action committees (PACs) that raised and spent money to influence the elections — American Mission and Building the Future — collectively spent $4.8 million to back South Carolina Senate candidate Darline Graham, who lost. American Mission is the Republican spending arm ofLeading the Future(LTF), a broader political group backed by OpenAI president Greg Brockman and the VC firm Andreessen Horowitz. American Mission also spent more than $500,000 apiece supporting Republican House candidates Aaron Flint in Montana and Laurie Buckhout in North Carolina, both of whom lost. LTF’s Democratic spending arm, Think Big, had better luck backing Florida Rep. Jared Moskowitz, who won reelection. Groups advocating for stronger AI safeguards also saw mixed results.Public First,which is backed by Anthropic, supported several Republicans who lost through its affiliated PAC but had more success backing Democratic candidates. It also contributed $3 million to a PAC supporting California state Sen. Scott Wiener, who was leading his race at the time of publication. Meanwhile,Guardrails Alliance, a group that has sought to make taking money from AI companies a political liability, spent more than $1 million apiece opposing two candidates who lost: California Rep. Jimmy Gomez and Montana’s Aaron Flint. It also spent $300,000 supporting Angela Gonzales-Torres, who defeated Gomez. It’s difficult to separate the impact of AI-related spending from the broader Democratic wave that swept Tuesday’s elections. Elon Musk, who reportedly poured half a billion dollars into supporting Republicans in the midterms, also sawmany of his candidates lose. Indeed, LTF also backed some candidates it believed were likely to win, only to see them lose to the Dems. For LTF, though, the general election wasn’t the main focus. The group told TechCrunch ahead of Election Day that it thinks primaries (the contests that choose each party’s nominee) are a more effective use of its money, because spending there can build name recognition and help candidates set up AI policy agendas. LTF spent $27.38 million in the primaries, including $8 million alone on opposing New York Assembly memberAlex Bores, who lost his bid for Congress back in June. When deciding whether it’s worth jumping into a general election race, LTF assesses how competitive the race is, whether it thinks spending could make a difference, and whether it should keep its powder dry for future elections. Charlie Blaettler, political director of Guardrails Alliance, had a different theory for why LTF spent comparatively little in the general election. “They don’t want their money to become an issue in these elections,” he said. He pointed to the Michigan Senate primary election, in which a pro-Israel lobbying group called AIPAC spent close to $30 million backing Democratic candidate Haley Stevens against Abdul El-Sayed. Stevens conceded the primary to El-Sayed, who went on to win the Senate seat. “AIPAC became the story in that race,” Blaettler said. “We know people hate AI billionaires. They hate the people running these companies. They’re very distrustful and disgusted by the political spending and lobbying that the tech industry does. If they spend in a competitive race, they would just become an enormous liability for their candidates.” The main fight among AI-related PACs, whether they are pro-industry or pro-regulation, is whether Congress should establish a national AI framework thatoverrides state laws, or whether states will maintain their own ability to impose safeguards. Neither side seems poised to back down. LTF, which favors a single national AI framework, told TechCrunch it plans to keep spending in the 2028 elections, while Guardrails Alliance says it wants to keep opposing candidates backed by the AI industry. Blaettler said that while LTF’s ads rarely touch on AI, instead focusing on popular issues for each candidate, Guardrail Alliance’s ads are specifically about who is taking money from the AI industry. “Our goal is to make AI money politically toxic,” Blaettler said.

The November 3 midterm results gave Democrats full control of Congress, setting the stage for what could be one of the most divided U.S. governments this decade, with Republicans in the White House. Tuesday’s results suggest that anger over data centers, the large facilities that house the computers powering AI, is becoming a political force. With Democrats now in control of Congress, that could lead to new limits on where data centers can be built and how much say local communities have. Data centers became a ballot-box issue in various states. AnNBC exit pollshowed how concerned voters are about AI: More than half of respondents believe that AI will do more harm than good, while almost 80% are against the building of data centers in their neighborhoods. Almost 60%, meanwhile, said data centers were acrucial or major factorin their vote. Nadine Smith, president and CEO of the racial justice organization Color of Change, called Tuesday’s election a referendum on “who this economy is built for.” “National security matters,” Smith said, referring to a common argument from data center supporters that the infrastructure is essential for the U.S. to stay ahead in war and in its rivalry with China. “And so do the families in South Memphis breathing exhaust from the gas turbines powering an AI supercomputer.” (She was referring to xAI’s data center in Memphis, Tennessee, which uses gas turbines for power.) Voters in several states pushed back against the AI buildout, even as pro-AI super PACs spent millions hoping to sway them this midterm. The anti-data center backlash was especially felt in states like Ohio, where OpenAI has eyed a $500 billion data center, backed by more than $100 billion in financing from Nvidia. In fact,the Ohio countywhere Meta had planned a 700,000-square-foot facility just passed a ban on data centers, and local communities across the state overwhelmingly voted against data center buildout measures. Analysts atMorgan Stanley predict thatDemocratic governor-elect Amy Acton will also pose a major risk to Ohio’s data center buildout. Elsewhere, candidates in Texas, Maine, Michigan, Nevada, Georgia, and South Carolina all won seats after taking a stance against the rapid buildout of data centers. “It is clear that money does not buy outcomes,” said Anshi Bhatt, a tech and policy researcher, adding that in modern politics, creating a “local villain” is one way to build campaign momentum. Likely next steps include more construction moratoriums or requiring data centers to pay for their own power grid upgrades instead of passing those costs on to nearby communities. Goldman Sachs, in fact, predicts data center construction delays in states like Georgia and Texas because of Democratic gains. Democratic control of Congress could also improve the odds for bills like the one Sen. Bernie Sanders and Rep. Alexandria Ocasio-Cortez introduced earlier this year, though any such bill would also face a possible veto. It proposes a nationwide moratorium on new data centers until Congress adds new guardrails and ensures that the buildout does not raise electricity costs, harm the environment, or proceed without community approval. There are also bills like the GRID Savings Act, proposed by New Mexico Sen. Martin Heinrich, which would prevent grid infrastructure costs from being passed on to communities during large AI data center buildouts. The environment is also a major concern, especially at xAI’s data center in Memphis and at the data centers throughout Virginia, known as the world capital of data centers, where gas turbines are used for power. Maia Woluchem, program director at Data & Society, a nonprofit research group, believes that changes to energy regulations, land rights, and other environmental policies could affect the data center buildout, especially as congressional Democrats look further into the Trump administration’s rollback of certain energy protections,as the New York Times reported they might. “Regardless of federal action, I could imagine that we will see additional movement at the state and local level, given the momentum that’s been building from the ground up,” Woluchem continued, citing governor-elect Gina Hinojosa, who supports a statewide moratorium on data centers, as an example. Both Hinojosa and Gov. Greg Abbott called for some limits, but Hinojosa centered much of her campaign on opposing data centers, a notable choice in Texas, whose electrical grid has proved vulnerable over the past decade. But the hard part is still to come. Smith, for example, is now expecting a fight, or even more executive orders, to bypass what Congress is now likely to block. “Even among Democrats, a blanket freeze is contested,” she said, referring to some Democrats’ worry that a moratorium could slow AI progress and hurt national security. She also expects AI lobbyists to start calling lawmakers. “Democrats ran on making Big Tech pay,” Smith said. “Our job is to make sure they remember it once the cameras leave.” The backlash runs deeper than the buildings themselves, which aren’t new. One private equity executive told me recently that people don’t necessarily hate data centers, but rather AI, and that data centers have become a stand-in for people’s fears and anxieties about the technology. “It does look like the results are pointing to a real frustration with tech power at minimum,” Woluchem said, noting that this is also a bipartisan issue. For the past month, people have told me they are worried about data centers’ effect on the environment and about theirlack of sayin whether they’re built. Amazon, for example, built a data center in Gilroy, California,without many residents knowing, by satisfying a 45-year-old zoning law. Vague or outdated zoning laws, along with requirements that local officials sign nondisclosure agreements (NDAs) barring them from discussing data center projects, have only fueled people’s outrage about the buildout. Data centers have also received billions in tax breaks, and although many tech companies have touted the benefits, such asjobsand community programs, for many people, that simply wasn’t enough. People want to know they still have a say in what happens in their communities. Many also fear that AI buildouts will mainly enrich a few wealthy people while their communities suffer and living costs rise. “If AI infrastructure is truly a national priority, then the companies building it can afford to pay for their own power, meet clean air standards, disclose what they use, and build with the consent of the people who live next door,” Smith said. “Families should never be subsidizing the richest corporations in history through their utility bills.”

Apple is cutting the daily amount its engineering teams can spend on AI, BloombergreportedWednesday. It’s a big change for a company that has workedto integratethe technology into its engineering processes. In October, Apple lowered the daily AI spending cap for its engineering teams, decreasing it from $300 to $200, the outlet reported. And more cuts are in the works, with some allowances falling to $100 a day, sources tell Bloomberg. Outside engineering, Apple is reportedly weighing a daily limit as low as $25 a day. TechCrunch has reached out to Apple for comment. Earlier this year, atsunami of tokenmaxxingtook hold, with companies pushing staff to use AI as much as possible in the name of vaguely defined efficiency gains. The frenzy was short-lived, however, as bills for said tokens came due, and companies decided that token rationing might be a more fiscally sensible approach. Concerns persistabout an apparent gap between what AI costs to build and run and the (often unclear) productivity gains the technology is suppose to generate.
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The company will offer affected employees at least six months’ salary and consolidate more product teams in Sydney as part of an organisational restructuring.
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The model scored 71.8 across three benchmarks, recording a 44 ms response time on an NVIDIA B200 GPU.
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The company’s adjusted profit rose 20.7% year-on-year, while its proposed ITC Infotech merger remained on track.
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Their departures come as Claude Code expands its role in Anthropic’s AI coding business.
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Altman’s recent comment on RAM shortage has reignited the debate over memory allocation between AI data centres and consumer devices.
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The new capabilities give AI agents business context, enterprise controls and the ability to execute recurring tasks autonomously.
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