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This research update examines economic models predicting whether AI development will accelerate via feedback loops between model capabilities and R&D improvements, directly addressing the forecasting of frontier AI risks. By clarifying ambiguous definitions of recursive self-improvement to focus on "self-sustaining acceleration," the authors provide critical context for assessing the trajectory of future AI capabilities.

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The Economics of Recursive Self-Improvement

METRJuly 22, 20265 min read

Notes are unpolished research updates directly from METR researchers, and have gone through less review than our research posts. They do not necessarily reflect the views of METR as a whole. We (Parker and Tom) recently coauthored a paper, “The Economics of Recursive Self-Improvement”, with 7 other economists. The paper walks through a series of simple models of how AI may accelerate AI R&D, and we thought it’s worth highlighting some context and takeaways: We care about Recursive Self-Improvement (RSI) because we want to forecast capabilities. METR’s priority is to assess risk from frontier AI development, and one input is how capable AI systems…

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