I’m up for doing that. Are there any important things I should take into account before doing it? My first draft would be something like:
Will tailcalled consider X alignment approach important in 4 years?
With description:
I have been following AI and alignment research on and off for years, and have a somewhat reasonable mathematical background to evaluate it. I tend to have an informal idea of the viability of various alignment proposals, though it’s quite possible that idea might be wrong. In 4 years, I will evaluate X and decide whether there have been any important good results since today. I will probably ask some of the alignment researchers I most respect, such as John Wentworth or Steven Byrnes, for advice about the assessment, unless it is dead-obvious. At the time of making the market, I currently think <extremely brief summary>.
<link to core post for X>
List of approaches I would currently have in the evaluation:
Something roughly along those lines sounds right. You might consider e.g. a ranking of importance, or asking some narrower questions about each agenda—how promising will they seem, how tractable will they seem, how useful will they have been in hindsight for subsequent work produced in the intervening 4-year period, how much will their frames spread, etc—depending on what questions you think are most relevant to how you should allocate attention now. You might also consider importance of subproblems, in addition to (or instead of) agendas. Or if there’s things which seem like they might be valuable to look into but would cost significant effort, and you’re not sure whether it’s worthwhile, those are great things for a market on your future judgement.
In general, “ask lots of questions” is a good heuristic here, analogous to “measure lots of stuff”.
I considered that, but unless I’m misunderstanding something about Manifold markets, they have to be either yes/no or open-ended.
or asking some narrower questions about each agenda—how promising will they seem, how tractable will they seem, how useful will they have been in hindsight for subsequent work produced in the intervening 4-year period, how much will their frames spread, etc—depending on what questions you think are most relevant to how you should allocate attention now [...]
In general, “ask lots of questions” is a good heuristic here, analogous to “measure lots of stuff”.
I agree with measuring lots of stuff in principle, but Manifold Markets only allows me to open 5 free markets.
I’m up for doing that. Are there any important things I should take into account before doing it? My first draft would be something like:
With description:
List of approaches I would currently have in the evaluation:
Natural Abstractions
Infrabayes
Shard Theory
Brain-like AGI
Something roughly along those lines sounds right. You might consider e.g. a ranking of importance, or asking some narrower questions about each agenda—how promising will they seem, how tractable will they seem, how useful will they have been in hindsight for subsequent work produced in the intervening 4-year period, how much will their frames spread, etc—depending on what questions you think are most relevant to how you should allocate attention now. You might also consider importance of subproblems, in addition to (or instead of) agendas. Or if there’s things which seem like they might be valuable to look into but would cost significant effort, and you’re not sure whether it’s worthwhile, those are great things for a market on your future judgement.
In general, “ask lots of questions” is a good heuristic here, analogous to “measure lots of stuff”.
Markets up: https://www.lesswrong.com/posts/3KeT4uGygBw6YGJyP/ai-research-program-prediction-markets
I considered that, but unless I’m misunderstanding something about Manifold markets, they have to be either yes/no or open-ended.
I agree with measuring lots of stuff in principle, but Manifold Markets only allows me to open 5 free markets.