Deep learning pioneer Bengio argues the training process itself makes AI dangerous
AI researcher Yoshua Bengio is adding his voice to a growing chorus of warnings about AI safety, arguing that advanced AI agents could spiral out of human control. In a new essay, he warns that the better AI agents get at optimizing goals, the better they also get at deceiving users, gaming rules, coordinating with each other , and hiding bad behavior . Bengio says this behavior emerges from the training process itself, from imitating human text through reinforcement learning , and that poorly defined goals can push systems to optimize against human intent. Anthropic's research supports his view.
The deep learning pioneer has called for years to slow AI progress and only train or deploy models after independent safety reviews, and about a year ago founded LawZero to build safer AI systems. Many of the recent warnings have come from inside the AI labs themselves, fueling talk of an industry-wide slowdown .
But Donald Trump disagrees . The US president sees no threat and wants to keep outpacing China, warning the US could end up in a "very bad position" if it doesn't win the AI race . Ad Ad
AI News Without the Hype – Curated by Humans
Subscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive "AI Radar" frontier report six times a year, full archive access, and access to our comment section.