AI Watch

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Connecting the dots: Generative AI has been blamed for hundreds of thousands of layoffs over the past year, but evidence that companies moved too quickly to automate white-collar jobs is steadily mounting. Multiple recent studies suggest that many employers are refilling recently eliminated positions after overestimating AI’s productivity gains and cost savings.

In some studies, roughly a third of companies that attempted to replace workers with AI have either rehired some of them or expressed regret over the decision. The figures add to a growing body of evidence that the true cost of implementing generative AI is catching businesses off guard.

A late 2025 report from Forrester Research predicted that roughly half of AI-attributed layoffs would be quietly reversed. However, the so-called AI boomerang effect may not benefit all workers equally.

While firms might quietly rehire experienced employees, those seeking entry-level jobs may still be out of luck. Forrester also predicted that most companies will use the opportunity to pivot to cheaper offshore labor.

Meanwhile, Gartner published research in February predicting that half of the businesses that eliminated customer service positions will rename and refill them by 2027. The forecast accompanied a separate October 2025 survey of 321 customer service and support leaders, which found that only 20% had actually reduced headcount while pivoting to AI – suggesting automation has largely augmented workers rather than replaced them.

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The buzziest bit of the new artificial-intelligence bill from Reps. Jay Obernolte, a California Republican, and Lori Trahan, a Massachusetts Democrat, is probably the section that would let Washington preempt state rules on AI development for three years. For me, the more interesting part is its bet on auditing as a middle path between Silicon Valley self-regulation and an FDA-style premarket approval regime for frontier models.

Earlier this year, several dozen AI policy folks signed onto a proposal, “Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies” that “outlines a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers’ safety and security claims, and evaluation of their systems and practices against relevant standards, based on deep, secure access to non-public information.”

What does that mean? For starters, an audit is not a permission slip. Rather than making a company clear a government gate before shipping, as the FDA does with drugs, an independent reviewer with access to the confidential innards of an AI company would check the latest model against a set standard. Think of it as how an accountant signs off on a public company’s books. Private firms do the examining while a public body stays in the background. Maybe it sets the rules, accredits the examiners, and holds the enforcement hammer.

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One congressman is moving to protect the soft underbelly of America’s critical infrastructure with a new bill.

Republican Tennessee Rep. Matt Van Epps unveiled a House version of Sen. Tom Cotton’s Critical Infrastructure Airspace Defense Act Tuesday, which aims to shield hospitals, power plants, water treatment sites, and dams from potential drone attacks. The bill would make grants available to private companies to purchase government-approved anti-drone technologies, and could even extend to data centers.

“The bill gives the Secretary of Homeland Security, in consultation with the Secretary of Energy and others, the ability to determine which critical infrastructure facilities need these authorities,” Van Epps told the Daily Caller News Foundation. “This could include anything from critical water systems to power plants and potentially even data centers.”

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Rep. Jay Obernolte has an aggressive timeline for getting his new bipartisan Artificial Intelligence proposal taken up in the House — and a path for getting a congressional hearing on a major part of the plan.

In an interview Monday night, the California Republican said he hoped to turn the draft framework he unveiled last Thursday into multiple bills, with the first expected to be introduced in the coming weeks. Each bill would be considered by its committee of jurisdiction.

“One of the challenges that we have is that the bill crosses so many different policy committee jurisdictions,” he said. “So I think we’ve got to divide it up into different titles that are in the jurisdiction of various policy committees and hear those individually.”

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The UK government has laid out a $1.47 billion plan to shake its dependence on foreign-made artificial intelligence hardware.

Under the measures, announced Monday, the UK will spend more than $1 billion on a national AI supercomputer. It will be stocked with $530 million worth of hardware, including $200 million that will go toward specialist inference chips for processing AI tasks. Priority will be given to up-and-coming British firms in the procurement process; the government pointed to Olix and Fractile, two UK startups developing new styles of inference chip, as potential beneficiaries. British researchers and startups are expected to be able to use the supercomputer starting in 2030.

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As A.I. systems become more agentic and take on more autonomy in daily life, they will increasingly interact with one another rather than with humans, according to Amanda Askell, Anthropic’s resident philosopher. “Human input is going to be rarer and rarer. That’s the thing that we need to prepare models for,” Askell said at the Bloomberg Tech Summit in San Francisco last week. Askell’s non-technical role reflects a growing trend among leading A.I. labs to incorporate humanities expertise. But she also sees a future in which A.I. may be able to do her job better than she can. “What [A.I. models] are good at is these deeply human skills,” she said. “Eventually, Claude is going to be a much better philosopher than I am, and probably be much better at every aspect of my job than I am.”

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The CEOs of several major artificial intelligence companies are urging members of Congress to adopt new laws that would make it harder for bad actors to develop biological weapons using their technology.

Google DeepMind’s Demis Hassabis, OpenAI’s Sam Altman, Anthropic’s Dario Amodei, and Microsoft AI’s Mustafa Suleyman are among the signatories on a public letter calling for laws requiring companies that sell synthetic DNA and RNA to screen customers and orders to prevent the misuse of genetic material.

Organized by the nonpartisan Institute for Progress and the right-leaning Foundation for American Innovation, the letter acknowledges that given the pace of AI development, “there is a real possibility that the knowledge barriers which have historically prevented bad actors from obtaining biological weapons will meaningfully erode.”

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The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The EU has proposed new legislation to end its Big Tech dependence
The laws aim to boost domestic ​cloud, AI and semiconductors. (CNBC)
+ US firms would be blocked from critical public tenders. (Reuters $)
+ It also wants to make sure non-EU actors cannot disrupt tech services with a “kill switch.” (The Guardian)
+ But the proposal needs to be negotiated with EU member states. (Politico $)

2 Intelligence agencies warn Chinese spies are recruiting on LinkedIn
The Five Eyes alliance said Beijing is using job platforms for espionage. (BBC)
+ The spies are allegedly recruiting government and military staff. (Politico $)
+ The Chinese embassy in the UK condemned the accusations. (Bloomberg $)
+ Meet the man hunting the spies in your smartphone. (MIT Technology Review)

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China’s plan to become a world leader in AI by 2030 is a fixture of practically every Congressional briefing and expert commentary on Beijing’s AI ambitions. The plan’s logic — introduced in 2017 — was simple and alarming: Beijing would direct capital, mobilize its firms, recruit talent, and execute with the strategic patience of a state-led innovation ecosystem. Nearly a decade later, that frame has only hardened. Beijing’s recently issued 15th Five-Year Plan directs Party organs to take “extraordinary measures” to strengthen technological self-reliance and launch a new “AI+” initiative to integrate AI across the nation’s strategic sectors. Beijing has the legal architecture to compel its firms to do its bidding, so Washington has largely concluded that Beijing’s AI sprint reflects deliberate industrial policy, and built America’s response around that assumption.

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A new study shows that computer malware powered by easily accessible artificial intelligence models is here—the research is a “wake-up call” to take cybersecurity risks from AI more seriously, one expert says.

In the study, researchers created an AI-powered computer “worm” designed to attack and spread between devices—revealing a threat that they say the world is woefully underprepared to fight.

“Our results demonstrate that self-sustaining AI-driven cyber-threats are no longer theoretical,” the researchers wrote. The paper, first reported by the New York Times, was posted on the preprint server arXiv.org and has yet to be peer-reviewed.

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President Donald Trump has signed a scaled-back version of an executive order governing AI that he had shelved less than two weeks ago, after senior aides persuaded him that the administration could not indefinitely delay establishing a framework for the technology, according to two officials familiar with the matter.

The revised order gives the federal government access to the most advanced artificial intelligence models 30 days before their public release, down from an earlier proposal that would have required companies to provide access 90 days in advance.

Beyond shortening the review period, the administration made few substantive changes to the original text. Trump approved the revised order Monday night following a high-level White House meeting. Aides drafted the final language Tuesday morning, the two officials tell WIRED.

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On Monday, SpaceX amended its initial public offering to state that water conditions—including water scarcity, regulations around water, and drought—could constrain data center development.

It isn’t the only tech company trying to assess how water scarcity might impact its business. Water use is emerging as one of the most contentious data center issues. A recent Gallup poll found that seven out of 10 Americans are opposed to data center development, with water scarcity ranking as the top resource concern. Facing increasingly fierce resistance, some tech companies are scrambling to assure the public that they’re facing the issue head-on.

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G­­­ross domestic product advanced 0.3% in the first three months of the year, just one-third of the pace recorded in the final quarter of 2025 and missing estimates, government data showed Wednesday. Private investment climbed by almost 4%, led by higher outlays on data centers, with a 16% jump in spending on machinery and equipment the largest gain in almost 30 years.

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For months, the loudest voices in artificial intelligence—including OpenAI’s Sam Altman and Anthropic’s Dario Amodei—warned that entry-level white-collar jobs were headed for extinction. In recent weeks, both have walked back those statements.

And according to Cognizant CEO Ravi Kumar S., who oversees a workforce of more than 350,000 employees, the outcry wasn’t just a prediction gone wrong—it was fearmongering.

“There was a little bit of fearmongering from reading about the fact that there’s going to be a collapse of jobs,” Kumar said at Fortune’s COO Summit in Scottsdale, Arizona on Monday. “I think there will be more jobs.”

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In April, a former contributor to the Beijing Normal University student media outlet 京师学人 (Jīngshī Xuérén, “Capital Scholar”) noted that its WeChat public account had been deregistered. Although updates had halted in 2023, the account and its content—more than 600 existing articles—had remained online, and “The Snowman” (雪人 Xuěrén, a pun on 学人 Xuérén) was warmly remembered as an eccentric campus institution and a training ground for emerging journalism students. News of its final demise prompted reflection and criticism online.