Measuring AI R&D Automation

ArXi:2603.03992v3 Announce Type: replace-cross The automation of AI R&D (AIRDA) could have significant implications, but its extent and ultimate effects remain uncertain. We need empirical data to resolve these uncertainties, but existing data (primarily capability benchmarks) may not reflect real-world automation or capture its broader consequences, such as whether AIRDA accelerates capabilities than safety progress or whether our ability to oversee AI R&D can keep pace with its acceleration.