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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders
Sam Altman and Dario Amodei are both walking back their A...
Sasha Rogelberg · 2026-05-27 · via Hacker News - Newest: "AI"

Two of the most influential CEOs in tech spent the last year warning that AI would gut white-collar employment. Now they’re admitting they were wrong, joining other leaders like Goldman Sachs CEO David Solomon in casting doubt on an AI job apocalypse. 

OpenAI CEO Sam Altman, in an interview with Commonwealth Bank of Australia CEO Matt Comyn on Tuesday, said he was “pretty wrong” about AI’s economic impact—a reversal from his June 2025 warnings that entry-level roles were at serious risk. Anthropic CEO Dario Amodei, who once claimed AI could eliminate 50% of white-collar jobs, now says automation may actually expand the work people do. Solomon, meanwhile, has argued consistently since at least late 2025 that the panic was overblown—and is now pointing to a century of American economic history to say he was right.

“I’m delighted to ⁠be wrong about this,” Altman told Comyn. “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than ​has actually happened.”

Altman added that he’s taken a lot of flack for his hype, but better safe than sorry.”People are like, ‘Oh you could have saved the world a lot of fear mongering and a lot of doom and gloom’ but at the time I was like, ‘I see this is a real risk we should probably ​talk about it.’ and it still may.”

Both OpenAI and Anthropic are reportedly preparing to launch their respective IPOs this year, each company with an estimated valuation of $1 trillion.

Two reversals and a vindication

For the OpenAI CEO, his comments walk back his prophecy on AI’s impact on labor. A year ago, Altman told his brother Jack on the Uncapped podcast: “A lot of jobs will go away…we have always been really good at figuring out new things to do…I’m not a believer that that ever runs out.” 

Now he says the displacement he feared simply hasn’t materialized, and a personal experiment reinforced it. He tried delegating his Slack and email responses to AI, then began responding to come again manually.

“We really do care about our interactions with people,” he said. “This thing…is not something that I can imagine myself outsourcing to an AI anytime soon. It really updated me to thinking that the jobs picture is likely to be very different than we thought.”

Amodei’s evolution has been similarly dramatic. While he previously claimed AI could wipe out 50% of white-collar jobs, he reframed automation earlier this month not as a destroyer of jobs but a multiplier of output: “If you automate 90% of the job, then everyone does the 10% of the job,” he said, offering a prediction similar to those made by economists Alex Imas and Tyler Cowen. “And the 10% kind of expands to be 100% of what people do and kind of 10-times their productivity.”

Solomon, meanwhile, didn’t need to change his position because he never held the apocalyptic one. In a recent New York Times op-ed, he offered the same argument he has made since at least late 2025: that American history offers a clear rebuttal to AI job panic, drawing a straight line from the electrification of the 1900s to the digital revolution of the 1990s to today: “The United States has a long track record of creating new jobs in response to disruption … I don’t see any reason to think this dynamic will stop now.”

Despite sectoral shifts, Solomon noted, civilian U.S. employment has grown 145% since 1962. He cited Goldman Sachs research showing data center construction alone has added 200,000 jobs since 2022. A 2018 study by Nobel laureate Daron Acemoglu backs his claim, finding that AI’s displacement effect is typically offset by productivity-driven demand for labor.

“Do any of us feel like we have less to do these days despite the convenience of Excel, email or Zoom?” Solomon said.

What the data shows and what it doesn’t

The data offers a mixed picture. Tech layoffs through May 2026 have passed 115,000, already approaching the 124,000 logged in all of 2025, with Meta, Amazon, and Snap among those citing AI as a driver of cuts. Yet the Yale Budget Lab has found no significant changes in occupational mix or unemployment duration in high-AI-exposure jobs since ChatGPT launched in late 2022.

Tech leaders have been issuing their own predictions on the future of work for years, ranging from AI being able to automate most white-collar work within 18 months, according to Microsoft AI CEO Mustafa Suleyman to Nvidia CEO Jensen Huang’s belief that AI will not have an impact on the number of jobs, but will instead create opportunities for efficiency that will benefit employees leaning into the technology.

Business leaders and economists have started to come to a consensus on why AI could indeed be a boost for labor. In a LinkedIn post in response to Solomon’s op-ed, Box CEO Aaron Levie said he’s betting that Solomon will be proved correct. “If you looked at what work looked like a few decades ago and saw how much faster everything is or easier it is to produce today — even before AI — you’d certainly have been convinced there’d be no jobs left. Yet the opposite has happened. Why?” The answer, he offered, is that automation will not decrease demand for a certain role, but rather increase it, as automation will deliver “the same value proposition, but cheaper.” 

It’s essentially the theory of Jevons paradox that Anthropic’s Amodei and economists like Apollo’s Torsten Slok have also called up in explaining the future of labor. Named for English economist William Stanley Jevons, the paradox refers to the period following the invention of the Watt steam engine, when instead of more efficient coal burning resulting in less coal being burned, the commodity instead became cheaper and more popular. Slok has noted professions like call center employees and radiologists, both with roles vulnerable to automation, have remained steady or increased despite wider AI adoption.

“Lower cost per interaction does not mean fewer interactions,” Slok said in a recent blog post. “It means more customers served, more channels opened and more markets worth reaching. The technology that was supposed to shrink the industry is fueling its expansion.”