How an assessor could investigate evidence of acceleration from the automation of AI R&D

This article discusses how an assessor could study whether capabilities progress could accelerate dramatically due to AI-driven acceleration of AI R&D. Such an assessment would answer: Capabilities Progress: How fast are internal capabilities improving, and how much has this progress accelerated recently? Acceleration from AI: If there is an acceleration, how much was it driven by AI automation versus other factors? Bottlenecks to Future Growth: Are there important bottlenecks that could slow growth or limit acceleration in the near term? Limitations: Would these methods reliably identify much more dramatic acceleration if it had occurred? Assessing this would involve analyzing capabilities of unreleased models, understanding the growth of key AI R&D inputs (labor, compute, data, and algorithms), and talking openly with relevant researchers about how AI is impacting their work. More details on access below. To understand whether capabilities progress has accelerated, the assessor must obtain data on…