The Economics of Recursive Self-Improvement
METR researchers coauthored a paper analyzing how AI might accelerate its own R&D through feedback effects, sometimes referred to as recursive self-improvement (RSI). The paper decomposes these feedback effects and highlights uncertainty about whether AI capabilities growth will accelerate or plateau due to various bottlenecks. It also clarifies the different definitions of RSI and focuses on the strength of feedback for forecasting future capabilities.
Why it matters: This analysis informs forecasts of AI capabilities growth, which is important for assessing future AI risk.
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