Arthur Conmy
Arthur Conmy's MATS Stream focuses on evaluating interpretability techniques on current and future AI Safety problems.
This can involve creating new safety techniques, as well as creating benchmarks and measuring performance against baseline techniques.
Stream overview
I am broadly interested in research directions scholars are excited about, that can advance the quality of our AI Safety tools, and our confidence in them. Three particular areas of research that seem promising to me are:
- Reasoning Model Interpretability
- Eliciting Strange Behaviors from Models 'in the wild' (i.e. not by training model organisms)
- Model Organisms too :)
London
Mentors
Arthur Conmy is a Member of Technical Staff at Anthropic. His interests are in automating interpretability, finding circuits and making model internals techniques useful for AI Safety, particularly with Sparse Autoencoders. Previously, he worked at Google DeepMind and Redwood Research (and did the MATS Program!).
Fellows we are looking for
Executing fast on projects is highly important. But also having a good sense of which next steps are correct is also valuable, though I enjoy being pretty involved in projects, so it's somewhat easier for me to steer projects than it is for me to teach you how to execute fast from scratch. It helps to be motivated to make interpretability useful, and use it for AI Safety, too.
I will also be interviewing folks doing Neel Nanda's MATS research sprint who Neel doesn't get to work with.
Project selection
Mentor(s) will talk through project ideas with scholar.