Intelligence explosion research series
Five research-backed essays on AI automating AI research: feedback loops, evidence, bottlenecks, oversight, and who benefits.
When AI Improves the Process of Improvement
How automated AI research could create a recursive feedback loop, what existing experiments demonstrate, and how to test whether improvements truly compound.
What the Evidence Actually Shows About AI Automating AI Research
A source-backed examination of AI research automation: company disclosures, METR evaluations, developer productivity, PostTrainBench, and the gaps between capability and acceleration.
The Bottlenecks Between Recursive Improvement and an Intelligence Explosion
The compute, data, research-return, and verification constraints between AI self-improvement and an intelligence explosion, with a checked sensitivity analysis of the CASP model.
Can Oversight Keep Up With AI Research?
How to evaluate oversight as AI research accelerates: intervention timing, independent evidence, agent reliability, and controlled promotion of research outputs.
Who Benefits When the Machines Accelerate Discovery?
Who gains from faster AI discovery? A research-backed analysis of economic adoption, concentrated power, institutional capacity, and preparation across three scenarios.