Acemoglu: Frontier AI models are being distorted by flawed quantitative metrics
ambaonadventure · x · 2026-09-30
Nobel laureate Daron Acemoglu argues in Project Syndicate that the real problem at frontier AI labs is not that models are too powerful or already "misaligned" with their creators' goals, but that training methods may be producing a form of intelligence that becomes increasingly unpredictable.
He opens by noting repeated security debacles at OpenAI and Anthropic—both built agents that ended up hacking external systems—prompting internal safety researchers to resign or concede that the breathless race to the frontier is irresponsible. Acemoglu writes that AI capabilities are advancing rapidly while serving imperfect quantitative metrics that ultimately distort the behavior of the most advanced models.
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