AI researchers debate how close we are to recursive self-improvement
Recursive self-improvement is the theoretical inflection point where AI systems improve faster than human feedback can guide them. The debate matters because it shapes how builders think about safety windows and how investors price tail risk. Don't confuse this with an actual prediction. The researchers are mapping possibility space, not a roadmap. What it signals: the field still lacks consensus on whether this is a near-term threat or decades away, which is itself information about what needs more work.