Why AI researchers keep building something they think will kill humans
AI researchers and industry leaders are debating the existential risks posed by recursive self-improvement in AI models. While some experts warn of catastrophic outcomes, investors and executives dismiss these concerns as distractions from the technology's commercial potential.
Why it matters
The tension between AI safety concerns and rapid commercial deployment highlights a critical ethical and regulatory crossroads for the tech industry.
A masked protester holds a placard saying 'Skynet Just Woke Up' in reference to the Terminator movies in London during a 2021 anti-lockdown demonstration. ZUMA Press Wire via Reuters Connect A version of this story originally appeared in the AI Insider newsletter. Sign up for the weekly AI Insider newsletter here . On Tuesday, OpenAI CFO Sarah Friar headlined a packed Goldman Sachs tech conference in San Francisco. One thing she said really stood out to me: The company's biggest models can now train other smaller models, helping OpenAI save on the huge costs of training these systems. This is an example of recursive self improvement, or RSI, where AI gets so powerful it can create the next, even more powerful, system itself. For the Wall Street analysts and investors around me at the Goldman conference, this sounded like an amazing business opportunity.
Also covering this story
8 other newsrooms covered this event. We read each version separately.
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