I currently think the interaction of important factors might be the biggest payoff; there don’t appear to be any methods currently available for learning about it otherwise. Granted, it will be extremely low-resolution, but being able to see interactions at all still feels like a good step.
This one feels clearer to me than most of the other potential benefits, so I’d be interested in understanding your thinking better. In particular, why do you think getting larger lists of possibly important things would be more likely than seeing interactions of the list we currently have (did I infer that right?)?
If you start with the objective of having an accurate understanding of one specific interaction, then you can probably do a better job of it, than if having this accurate understanding is a small piece of a larger task (like roleplaying an actor with 20 different strategic options and seeing how they win).
I think that in order to execute that strategy, we need to have clearly identified the things which are doing the interacting; this is what allows us to be specific about the interaction we are studying in the first place. It appears to me the problem is that we don’t have the ability to be specific in the interactions we are testing; indeed we don’t even have a good grasp of the space of variables.
So moving towards figuring out the space of the problem, in the High Dimensional World sense, is what I think we can get out of it. I think what I am proposing here is using plausible interactions as a detection mechanism, where I really just mean “this seems like something that could happen in real life” level plausible.
So in short, I agree with you about the benefits of wargaming; I think this is covered under a). Once we get the problem defined well enough, we’ll be able to employ the sub-problem strategy effectively.
The other central benefit I see is that the events of the game are common knowledge to the players, which is super difficult to achieve, based on my reading of the MIRI Conversations posts. I think it will make conversations between the players on the subject faster and more efficient as a result.
I currently think the interaction of important factors might be the biggest payoff; there don’t appear to be any methods currently available for learning about it otherwise. Granted, it will be extremely low-resolution, but being able to see interactions at all still feels like a good step.
This one feels clearer to me than most of the other potential benefits, so I’d be interested in understanding your thinking better. In particular, why do you think getting larger lists of possibly important things would be more likely than seeing interactions of the list we currently have (did I infer that right?)?
I think this is the most relevant crux:
I think that in order to execute that strategy, we need to have clearly identified the things which are doing the interacting; this is what allows us to be specific about the interaction we are studying in the first place. It appears to me the problem is that we don’t have the ability to be specific in the interactions we are testing; indeed we don’t even have a good grasp of the space of variables.
So moving towards figuring out the space of the problem, in the High Dimensional World sense, is what I think we can get out of it. I think what I am proposing here is using plausible interactions as a detection mechanism, where I really just mean “this seems like something that could happen in real life” level plausible.
So in short, I agree with you about the benefits of wargaming; I think this is covered under a). Once we get the problem defined well enough, we’ll be able to employ the sub-problem strategy effectively.
The other central benefit I see is that the events of the game are common knowledge to the players, which is super difficult to achieve, based on my reading of the MIRI Conversations posts. I think it will make conversations between the players on the subject faster and more efficient as a result.