This stream focuses on empirical AI control research, including defending against AI-driven data poisoning, evaluating and attacking chain-of-thought monitorability, and related monitoring/red-teaming projects. It is well-suited to applicants already interested in AI safety with solid Python skills, and ideally prior research or familiarity with control literature/tools (e.g. Inspect/ControlArena).
Alan Cooney leads the Autonomous Systems workstream within the UK's AI Safety Institute. His team is responsible for assessing the capabilities and risks of Frontier AI systems released by AI labs such as OpenAI, Google and Anthropic. Prior to working in AI safety, he was an investment consultant and start-up founder, with his company Skyhook being acquired in 2023. He also completed Stanford’s Machine Learning and Alignment Theory Scholars Programme, where he was supervised by Google DeepMind researcher Neel Nanda.
1-hour weekly meetings for going through your research log & high level guidance. Daily updates on slack are also very useful and I typically reply within 2 days to any questions.
Essential:
You may be a good fit if you also have some of:
Not a good fit:
Collaborating with other MATS scholars.
By default I'll propose several projects for you to choose from, but you can also pitch ideas that you're interested in.