Chollet on X: The Problem With Current AI Safety Framing

Chollet argues that much of the AI safety discourse is premised on a misunderstanding of what current systems can do. Fears of misaligned superintelligence assume a system that can generalize from limited goals to arbitrary capability — exactly the kind of generalization that ARC demonstrates current systems cannot perform. This doesn't mean AI is safe; it means the actual risks are different from the speculative superintelligence risks, and misidentifying the risk leads to misallocated safety research. Chollet advocates for safety research focused on real and present harms (bias, misuse, economic disruption) rather than speculative existential scenarios premised on capabilities systems don't yet have.