Empirical econ - applied AI transition for quantitative econometrician

This is a direct bet on talent entering the AI safety field. I am a first year Oxford PPE student and an EV fellow. I research quantitative measurement under messy, adversarial, and real world data (arms/drug trafficking, sanctions, money laundering). I've already built and run reproduction, re-estimation, and zero-hallucination information pipelines for both technical econometrics (spatial spillovers detection in top-7 journal work) and organised crime (a European Firearms Monitor). This grant would fund me in order to apply my methods toward AI safety and to close the gap between myself and a full-time safety researcher.

Over 6 months, alongside my degree, I'll complete a self directed curriculum in empirical alignment, including model organisms and dangerous capability evaluations in particular, and ship a concrete, legible output, with a focus on independent reproducibility of public-safety relevant evaluations, recomputing headlines with proper statistical power and testing if verdict survive planted positives.

The envisioned trajectory for the long run is a top research fellowship in the next available cycle, for which this output would be the qualifying artefact. This is a solo project.