Luca Righetti
This stream is primarily interested in mentoring projects in biosecurity that either (1) create rigorous threat models of AI biological misuse or (2) create benchmarks and tools that allow us to evaluate and mitigate these risks, as well as verifying that companies are taking suitable precautions.
Stream overview
Potential example projects for this stream include:
- Threat Model: What do inference compute trends imply for how fast dangerous biological capabilities may proliferate and become harder to monitor?
- Evaluations: Formalizing "scientific ideation in an empirical field" in a manner that allows one to assess human and LLM-generated hypotheses for novelty, plausibility, etc.
- Mitigations: Developing a way to more richly assess and describe the "blast radius" or "collateral damage" of efforts to remove-in-pretraining or unlearn material from LLMs
- Verification: How are we better able to standardize and compare the effectiveness of classifiers from different AI companies and assess how much they reduce misuse risk?
Mentors
Mentorship style
Typically, this would include weekly meetings, detailed comments on drafts, and asynchronous messaging.
Fellows we are looking for
For threat modeling work: Skeptical mindset, transparent reasoning, analytical
For evaluations, mitigations, and verification work: LLM engineering skills (e.g., agent orchestration), biosecurity knowledge
Mentorship will be a collaboration between me and my team at GovAI. The specifics depend on the candidate and project.
I am based in Berkley -- and some of my team is based in London.
Project selection
Mentor(s) will talk through project ideas with scholar
The Winter 2027 cohort offers a wide range of research streams led by experts across AI alignment, interpretability, governance, and safety. Each stream provides its own research agenda, methodology, and mentorship focus.
