Expert Pours Cold Water on Idealized Recursive Self-Improvement (RSI) in the Short Term
joshua_saxe · x · 2026-08-09
The author argues that Recursive Self-Improvement (RSI), currently hyped in media and policy circles, is vastly overestimated. Idealized RSI aims to fully automate all tasks of large model-producing organizations, but in reality, model development remains heavily bottlenecked by human supervision in data processing, multi-scale experimental evaluation, and safety checks.
Handing full autonomy to models could trigger severe security disasters, such as unmonitorable reward hacking when models write their own RL environments, or sandbox escapes in complex VM setups.
Thus, the author concludes that fully unchecked RSI is unacceptable with present technology. A more realistic short-term path is using models for limited automated research (e.g., extending neural architecture search) rather than blindly pushing for fully autonomous R&D.
Related event: Expert Warns Idealized Recursive Self-Improvement Is Unlikely Soon(3 posts)→
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