AI and work

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Why accessibility might be AI’s biggest breakthrough

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For those with visual impairments, language models can summarize visual content and reformat information. Tools like ChatGPT’s voice mode with video and Be My Eyes allow a machine to describe real-world visual scenes in ways that were impossible just a few years ago.

AI language tools may be providing unofficial stealth accommodations for students—support that doesn’t require formal diagnosis, workplace disclosure, or special equipment. Yet this informal support system comes with its own risks. Language models do confabulate—the UK Department for Business and Trade study found 22 percent of users identified false information in AI outputs—which could be particularly harmful for users relying on them for essential support.

When AI assistance becomes dependence

Beyond the workplace, the drawbacks may have a particular impact on students who use the technology. The authors of a 2025 study on students with disabilities using generative AI cautioned, “Key concerns students with disabilities had included the inaccuracy of AI answers, risks to academic integrity, and subscription cost barriers,” they wrote. Students in that study had ADHD, dyslexia, dyspraxia, and autism, with ChatGPT being the most commonly used tool.

Mistakes in AI outputs are especially pernicious because, due to grandiose visions of near-term AI technology, some people think today’s AI assistants can perform tasks that are actually far outside their scope. As research on blind users’ experiences suggested, people develop complex (sometimes flawed) mental models of how these tools work, showing the need for higher awareness of AI language model drawbacks among the general public.

For the UK government employees who participated in the initial study, these questions moved from theoretical to immediate when the pilot ended in December 2024. After that time, many participants reported difficulty readjusting to work without AI assistance—particularly those with disabilities who had come to rely on the accessibility benefits. The department hasn’t announced the next steps, leaving users in limbo. When participants report difficulty readjusting to work without AI while productivity gains remain marginal, accessibility emerges as potentially the first AI application with irreplaceable value.

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White House unveils sweeping plan to “win” global AI race through deregulation

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Trump’s plan was not welcomed by everyone. J.B. Branch, Big Tech accountability advocate for Public Citizen, in a statement provided to Ars, criticized Trump as giving “sweetheart deals” to tech companies that would cause “electricity bills to rise to subsidize discounted power for massive AI data centers.”

Infrastructure demands and energy requirements

Trump’s new AI plan tackles infrastructure head-on, stating that “AI is the first digital service in modern life that challenges America to build vastly greater energy generation than we have today.” To meet this demand, it proposes streamlining environmental permitting for data centers through new National Environmental Policy Act (NEPA) exemptions, making federal lands available for construction and modernizing the power grid—all while explicitly rejecting “radical climate dogma and bureaucratic red tape.”

The document embraces what it calls a “Build, Baby, Build!” approach—echoing a Trump campaign slogan—and promises to restore semiconductor manufacturing through the CHIPS Program Office, though stripped of “extraneous policy requirements.”

On the technology front, the plan directs Commerce to revise NIST’s AI Risk Management Framework to “eliminate references to misinformation, Diversity, Equity, and Inclusion, and climate change.” Federal procurement would favor AI developers whose systems are “objective and free from top-down ideological bias.” The document strongly backs open source AI models and calls for exporting American AI technology to allies while blocking administration-labeled adversaries like China.

Security proposals include high-security military data centers and warnings that advanced AI systems “may pose novel national security risks” in cyberattacks and weapons development.

Critics respond with “People’s AI Action Plan”

Before the White House unveiled its plan, more than 90 organizations launched a competing “People’s AI Action Plan” on Tuesday, characterizing the Trump administration’s approach as “a massive handout to the tech industry” that prioritizes corporate interests over public welfare. The coalition includes labor unions, environmental justice groups, and consumer protection nonprofits.

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The résumé is dying, and AI is holding the smoking gun

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Beyond volume, fraud poses an increasing threat. In January, the Justice Department announced indictments in a scheme to place North Korean nationals in remote IT roles at US companies. Research firm Gartner says that fake identity cases are growing rapidly, with the company estimating that by 2028, about 1 in 4 job applicants could be fraudulent. And as we have previously reported, security researchers have also discovered that AI systems can hide invisible text in applications, potentially allowing candidates to game screening systems using prompt injections in ways human reviewers can’t detect.

Illustration of a robot generating endless text, controlled by a scientist.

And that’s not all. Even when AI screening tools work as intended, they exhibit similar biases to human recruiters, preferring white male names on résumés—raising legal concerns about discrimination. The European Union’s AI Act already classifies hiring under its high-risk category with stringent restrictions. Although no US federal law specifically addresses AI use in hiring, general anti-discrimination laws still apply.

So perhaps résumés as a meaningful signal of candidate interest and qualification are becoming obsolete. And maybe that’s OK. When anyone can generate hundreds of tailored applications with a few prompts, the document that once demonstrated effort and genuine interest in a position has devolved into noise.

Instead, the future of hiring may require abandoning the résumé altogether in favor of methods that AI can’t easily replicate—live problem-solving sessions, portfolio reviews, or trial work periods, just to name a few ideas people sometimes consider (whether they are good ideas or not is beyond the scope of this piece). For now, employers and job seekers remain locked in an escalating technological arms race where machines screen the output of other machines, while the humans they’re meant to serve struggle to make authentic connections in an increasingly inauthentic world.

Perhaps the endgame is robots interviewing other robots for jobs performed by robots, while humans sit on the beach drinking daiquiris and playing vintage video games. Well, one can dream.

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