The technology may not be ready to replace workers, but that isn't stopping execs from pushing forward anyway. Late last month, at an event in Washington, D.C., Andrew Yang delivered a bleak message. "I have bad news, America," he told the crowd. The Fuckening is the name that Yang, a former presidential candidate, has given to AI's disembowelment of the workforce. As he sees it, millions of knowledge workers will soon lose their job, personal-bankruptcy rates will spike, and entire downtowns will turn vacant as offices hollow out.

Booth is a reporter at TIME. Booth is a reporter at TIME. Julian Pintat, a freelance English-to-German translator has watched his 15-year career gradually unravel. Specializing in high-stakes fields like medical technology and pharmaceutics, his expertise has been repriced as an AI cleanup service. Fixing such basic flaws, which now constitutes 95% of his work, often takes longer than translating from scratch, he says--a frustrating reality that has halved his income and put life plans including marriage and starting a family on indefinite hold.

Isla Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released. Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. "The number of people who were DMing me made us pretty excited," says Fulford. Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.

Shakked Noy and Whitney Zhang recruited 453 marketers, data analysts, and college-educated professionals and got each of them to complete two kinds of tasks they'd normally undertake as part of their jobs, such as writing press releases, short reports, or analysis plans. Half were given the option of using ChatGPT to help them complete the second of the two tasks. Each piece of work was evaluated by three people working in the same professions, hired through the research platform Prolific. The writers who chose to use ChatGPT took 40% less time to complete their tasks, and produced work that the assessors scored 18% higher in quality than that of the participants who didn't use it. The writers who were already skilled at writing were able to reduce the amount of time they spent on their work, while those who were assessed as being weaker writers produced higher-quality work once they gained access to the chatbot.

Artificial intelligence is slowly seeping into more and more areas of white-collar work. The latest crossover is between tax preparation firm H&R Block and IBM's Watson, with the former using IBM's AI chops to help quiz clients about their tax liabilities. When a customer visits H&R Block to prepare their returns, software powered by IBM will ask questions about their year -- looking for big events like selling a house or buying shares that might introduce tax-deductibles. It's a standard part of H&R Block's service, but the company hopes that by feeding Watson this data (along with answers provided by human tax preparers), they can improve performance across the board. H&R Block's George Gaustello told The Verge that the idea is to share expertise around the company. "We have 70,000 experts, but let's say 500 of those are very knowledgeable about firefighters, or they know every credit deduction a farmer can get," Gaustello tells The Verge.

Vox tech writer Timothy B. Lee used to be one of the most ardent techno-optimists. But he's had a bit of a conversion, of late, and is now on the side of those who think tech progress is slowing. Maybe it was the economist Robert Gordon who convinced him, or maybe years of observing the tech world changed his mind. In any case, Lee now broadly suggests that the inventions of tomorrow won't be as world-changing as those of yesteryear. There are a number of industries -- with health care and education being the most important -- where there's an inherent limit on how much value information technology can add.