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Former OpenAI and DeepMind employees warn of self-improving AI risks

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Several current and former OpenAI and Google DeepMind employees warned through video testimony from the AI safety nonprofit Palisade Research that companies are racing to build AI systems that can recursively self-improve without taking sufficient measures to prevent the risk of losing control; DeepMind research scientist Neel Nanda said the probability that AI causes human extinction is at least 10% and called that figure "absurdly high." The testimony was released by the project frominside.ai, and participants also said AI labs reward employees who develop new models more. Anthropic capability researcher Jacob Coxon publicly resigned on X on September 8, protesting the company's aggressive pursuit of AGI; New York Magazine and Asterisk magazine jointly interviewed eight employees who successively left OpenAI, Anthropic, and Google DeepMind, including Daniel Kokotajlo, Miles Brundage, Rosie Campbell, and others, whose reasons for leaving varied. According to a post by X user @themidasproj, in response to the conspiracy theory that "CEOs warn of catastrophic AI risk to protect big labs from competition through government regulation," the post points out that those truly worried are ordinary AI researchers in the private sector and academia.

Generated by AI from reports · Updated 4 days ago

Latest developments

3 developments
  1. · 1 reports
    Research shows AI researchers are more concerned about catastrophic AI risks than CEOs
    X @themidasproj:Research shows AI researchers are more concerned about catastrophic AI risks than CEOs
  2. · 1 reports
    Eight former lab employees on resigning to protest AI risks
    New York Magazine:Anthropic researcher Jacob Coxon resigns in protest: eight former OpenAI, Anthropic, and Google DeepMind employees on the decision to leave the lab
  3. · 1 reports
    Former OpenAI and DeepMind employees warn of self-improving AI risks
    Rappler:Former OpenAI and Google DeepMind employees warn: companies race to build self-improving AI while ignoring safety risks

Progress timeline

Oct 8
  1. X @themidasproj
    Research shows AI researchers are more concerned about catastrophic AI risks than CEOs

    According to a post by X user @themidasproj, in response to the conspiracy theory that "CEOs warn about catastrophic AI risks to use government regulation to protect big labs from competition," the post points out that it is ordinary AI researchers in the private sector and academia who are truly concerned.

Oct 5
  1. New York Magazine
    Anthropic researcher Jacob Coxon resigns in protest: eight former OpenAI, Anthropic, and Google DeepMind employees on the decision to leave the lab

    Anthropic capability researcher Jacob Coxon publicly resigned on X on September 8, protesting the company's aggressive pursuit of AGI. New York Magazine and Asterisk magazine jointly interviewed eight employees who left OpenAI, Anthropic, and Google DeepMind at various times, including Daniel Kokotajlo, Miles Brundage, Rosie Campbell, and others. Their reasons for leaving varied: some wanted to publicly warn about the risks of AI acceleration, some opposed their employers' cooperation with the Department of Defense, and some believed it was more valuable to do safety or employment-impact research externally.

  2. Rappler
    Former OpenAI and Google DeepMind employees warn: companies race to build self-improving AI while ignoring safety risks

    Multiple current and former employees of OpenAI and Google DeepMind, through video testimony via the AI safety nonprofit Palisade Research, warned that companies are racing to build recursively self-improving AI systems without taking sufficient measures to prevent the risk of losing control. DeepMind research scientist Neel Nanda said the probability that AI causes human extinction is at least 10%, and called this figure "absurdly high." The testimony was released by the project frominside.ai, and participants also said AI labs reward employees who develop new models more than those who call for caution.

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