We are focused on mathematical research and building bridges between academia and research. I think the pathway to doing that type of research is usually through traditional academic channels, a PhD program, or perhaps a masters degree or a program like MATS, at which point the type of research promotion and academic bridge building we are focused on become far more relevant. That said, we do have undergrad as an option, and are certainly OK with people at any level of seniority signaling their interest.

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[-]domenicrosati2y127

For my own clarity: What is the difference between mathematical approaches to alignment and other technical approaches like mechanistic interpretability work?

I imagine the focus is on in principal arguments or proofs regarding the capabilities of a given system rather than empirical or behavioural analysis but you mention RL so just wanted to get some colour on this.

Any clarification here would be helpful!

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[-]Vanessa Kosoy2y112

You are more or less right. By "mathematical approaches", we mean approaches focused on building mathematical models relevant to alignment/agency/learning and finding non-trivial theorems (or at least conjectures) about these models. I'm not sure what the word "but" is doing in "but you mention RL": there is a rich literature of mathematical inquiry into RL. For a few examples, see everything under the bullet "reinforcement learning theory" in the LTA reading list.

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