Yeah, my sense is that modern AI could be useful to tiling agent stuff if it were less liable to confabulate fake proofs. This generalizes to any technical branch of AI safety where AI could help come up with formalizations of ideas, proofs of conjectures, etc. My thinking suggests there is something of an “overhang” here at present, in the sense that modern AI models are worse-than-useless due to the way that they try to create good-looking answers at the expense of correctness.
I disagree with the statement “to some extent the goal of tiling-agents-like work was to have an AI solve its own alignment problem”—the central thing is to understand conditions under which one agent can justifiably trust another (with “trust” operationalized as whether one agent wants to modify the decision procedure of the other). If AI can’t justifiably trust itself, then it has a potential motive to modify itself in ways that remove safety guarantees (so in this sense, tiling is a precondition for lots of safety arguments). Perhaps more importantly, if we can understand conditions under which humans can justifiably trust AI, then we have a formal target for alignment.
True, I think your characterization of tiling agents is better. But my impression was sorta that this self-trust is an important precursor for the dynamic self-modification case where alignment properties need to be preserved through the self-modification. Yeah I guess calling this AI solving alignment is sorta confused, though maybe there’s sth into this direction because the AI still does the search to try to preserve the alignment properties?
Hm I mean yeah if the current bottleneck is math instead of conceptualizing what math has to be done then it’s a bit more plausible. Like I think it ought to be feasible to get AIs that are extremely good at proving theorems and maybe also formalizing conjectures. Though I’d be a lot more pessimistic about finding good formal representations for describing/modelling ideas.
Do you think we are basically only bottlenecked on math so sufficient math skill could carry us to aligned AI, or only have some alignment philosophy overhang you want to formalize but then more philosophy will be needed?
I think there is both important math work and important conceptual work. Proving new theorems involves coming up with new concepts, but also, formalizing the concepts and finding the right proofs. The analogy to robots handling the literal heavy lifting part of a job seems apt.
Yeah, my sense is that modern AI could be useful to tiling agent stuff if it were less liable to confabulate fake proofs. This generalizes to any technical branch of AI safety where AI could help come up with formalizations of ideas, proofs of conjectures, etc. My thinking suggests there is something of an “overhang” here at present, in the sense that modern AI models are worse-than-useless due to the way that they try to create good-looking answers at the expense of correctness.
I disagree with the statement “to some extent the goal of tiling-agents-like work was to have an AI solve its own alignment problem”—the central thing is to understand conditions under which one agent can justifiably trust another (with “trust” operationalized as whether one agent wants to modify the decision procedure of the other). If AI can’t justifiably trust itself, then it has a potential motive to modify itself in ways that remove safety guarantees (so in this sense, tiling is a precondition for lots of safety arguments). Perhaps more importantly, if we can understand conditions under which humans can justifiably trust AI, then we have a formal target for alignment.
Thanks.
True, I think your characterization of tiling agents is better. But my impression was sorta that this self-trust is an important precursor for the dynamic self-modification case where alignment properties need to be preserved through the self-modification. Yeah I guess calling this AI solving alignment is sorta confused, though maybe there’s sth into this direction because the AI still does the search to try to preserve the alignment properties?
Hm I mean yeah if the current bottleneck is math instead of conceptualizing what math has to be done then it’s a bit more plausible. Like I think it ought to be feasible to get AIs that are extremely good at proving theorems and maybe also formalizing conjectures. Though I’d be a lot more pessimistic about finding good formal representations for describing/modelling ideas.
Do you think we are basically only bottlenecked on math so sufficient math skill could carry us to aligned AI, or only have some alignment philosophy overhang you want to formalize but then more philosophy will be needed?
I think there is both important math work and important conceptual work. Proving new theorems involves coming up with new concepts, but also, formalizing the concepts and finding the right proofs. The analogy to robots handling the literal heavy lifting part of a job seems apt.