Measuring AI R&D Automation

Researchers propose new metrics to measure the automation of AI R&D (AIRDA), arguing that existing capability benchmarks don't capture real-world automation effects or broader consequences. The proposed metrics would track dimensions like capital allocation, researcher time, and AI oversight incidents to help decision-makers understand AIRDA's impact on AI progress and safety.