Research analyst at Open Philanthropy. Doctoral student in philosophy at the University of Oxford. Opinions my own.
Glad to hear you liked section 4.3.3. And thanks for pointing to these posts -- I certainly haven't reviewed all the literature, here, so there may well be reasons for optimism that aren't sufficiently salient to me.
Re: black boxes, I do think that black-box systems that emerge from some kind of evolution/search process are more dangerous; but as I discuss in 4.4.1, I also think that the bare fact that the systems are much more cognitively sophisticated than humans creates significant and safety-relevant barriers to understanding, even if the system has been designed/mechanistically understood at a different level.
Re: “there is a whole body of work which shows that evolved systems are often power-seeking” -- anything in particular you have in mind here?
Aren't they now defined in terms of each other?
"Intent alignment: An agent is intent aligned if its behavioral objective is outer aligned.
Outer alignment: An objective function r is outer aligned if all models that perform optimally on r in the limit of perfect training and infinite data are intent aligned."
Thanks for writing this up. Quick question re: "Intent alignment: An agent is intent aligned if its behavioral objective is aligned with humans." What does it mean for an objective to be aligned with humans, on your view? You define what it is for an agent to be aligned with humans, e.g.: "An agent is aligned (with humans) if it doesn't take actions that we would judge to be bad/problematic/dangerous/catastrophic." But you don't say explicitly what it is for an objective to be aligned: I'm curious if you have a preferred formulation.
Is it something like: “the behavioral objective is such that, when the agent does ‘well’ on this objective, the agent doesn’t act in a way we would view as bad/problematic/dangerous/catastrophic." If so, it seems like a lot might depend on exactly how “well” the agent does, and what opportunities it has in a given context. That is, an “aligned” agent might not stay aligned if it becomes more powerful, but continues optimizing for the same objective (for example, a weak robot optimizing for beating me at chess might be "aligned" because it only focuses on making good chess moves, but a stronger one might not be, because it figures out how to drug my tea). Is that an implication you’d endorse?
Or is the thought something like: "the behavioral objective such that, no matter how powerfully the agent optimizes for it, and no matter its opportunities for action, it doesn't take actions we would view as bad/problematic/dangerous/catastrophic"? My sense is that something like this is often the idea people have in mind, especially in the context of anticipating things like intelligence explosions. If this is what you have in mind, though, maybe worth saying so explicitly, since intent alignment in this sense seems like a different constraint than intent alignment in the sense of e.g. "the agent's pursuit of its behavioral objective does not in fact give rise to bad actions, given the abilities/contexts/constraints that will in fact be relevant to its behavior."