Build quantitative forecasts of China's indigenous compute production chain, refining existing DUV/EUV lag estimates and/or extending the approach to other bottlenecks such as HBM.
About the project
Estimates of China's semiconductor lag drive major policy conclusions (durability of export controls, race dynamics, timelines for compute governance). The AI Futures Project's forecast of Chinese DUV/EUV (blog.aifutures.org/p/a-forecast-of-chinese-duv-and-euv) gives a good baseline, but many considerations are not integrated into the forecast.
This project will (a) refine the lithography forecast, and/or (b) apply the same methodology to other bottlenecks: HBM, EDA tools, coater/developer machines. Output: a technical blog post with explicit probabilistic estimates and transparent reasoning.
Theory of change
"How long do export controls buy?" is arguably the highest-value open question in compute governance. Better forecasts can directly inform policy decisions and are reusable by the broader AI governance ecosystem.
Your role
Each mentee will own one bottleneck: build the causal decomposition, gather data, produce forecasts with explicit reasoning, and write up. We provide methodology, review, and policy framing.
Prerequisites
- Familiarity with the AI risk literature.
- Quantitative background; comfort with probabilistic forecasting (calibration, decomposition).
- Ability to do deep technical desk research on unfamiliar domains.
- Strong preference for French fluency for the policy-facing summary, written directly in French.
Application question(s)
- Suggest next steps for improving the forecasts in https://blog.aifutures.org/p/a-forecast-of-chinese-duv-and-euv.
- Link to any forecasting track record (Metaculus, etc.) or quantitative work sample.
About the mentors
Jérémy Andréoletti is Head of Research at the General-Purpose AI Policy Lab, where he works on risk modeling, forecasting, and governance for advanced AI systems. He completed a PhD at ENS-PSL on macroevolutionary Bayesian modeling and co-founded EffiSciences to support students and researchers interested in high-impact work (AI Safety, biosecurity).
After graduating in physics from EPFL in Switzerland, Antoine is now an AI Security Researcher at General-Purpose AI Policy Lab, a French research organization specializing in security and international coordination challenges posed by frontier AI models' development. His research focuses on foundational arguments for loss of control scenarios and on identifying concrete approaches to prevent them.