The Checklist: What Succeeding at AI Safety Will Involve
This piece reflects my current best guess at the major goals that Anthropic (or another similarly positioned AI developer) will need to accomplish to have things go well with the development of broadly superhuman AI. Given my role and background, it’s disproportionately focused on technical research and on averting emerging catastrophic risks.
For context, I lead a technical AI safety research group at Anthropic, and that group has a pretty broad and long-term mandate, so I spend a lot of time thinking about what kind of safety work we’ll need over the coming years. This piece is my own opinionated take on that question, though it draws very heavily on discussions with colleagues across the organization: Medium- and long-term AI safety strategy is the subject of countless leadership discussions and Google docs and lunch-table discussions within the organization, and this piece is a snapshot (shared with permission) of where those conversations sometimes go.
To be abundantly clear: Nothing here is a firm commitment on behalf of Anthropic, and most people at Anthropic would disagree with at least a few major points here, but this can hopefully still shed some light on the kind of thinking that motivates our work.
