Once again I really like this model Bob. I’m pretty excited to see how this model changes with even more time to iterate. I’d never come across the formalised idea of slack before and I think it describes a lot of what was in my head when responding to your last post!
I’m wondering how you’ve been thinking about marginal spending in this model? I.e, If we’re patient philanthropists, which choices should we spend money on and which should we save once we factor in that some choices are easier to affect than others? For example, one choice might be particularly hingey under any of your proposed definitions but be very hard for a philanthropist to affect; e.g the decisions made by one person who might not have heard of EA (either as a world leader or just being coincidentally important). We probably won’t get a great payoff from spending a load of money/effort identifying that person and would prefer to avoid that path down the decision tree entirely.
I guess the thrust of the question here is how we might account for tractability of affecting choices in this model. Once tractability is factored in me might prefer to spend a little money affecting lost of small choices which aren’t as hingey under this definition rather than spending a lot affecting one very hingey choice. If this is the case I think we’d want to redefine hingeyness to match our actual decision process.
It seems like each edge on the tree might need a probability or cost rating to fully describe real-world questions of traceability but I’d be very interested in yours or others thoughts.
Once again I really like this model Bob. I’m pretty excited to see how this model changes with even more time to iterate. I’d never come across the formalised idea of slack before and I think it describes a lot of what was in my head when responding to your last post!
I’m wondering how you’ve been thinking about marginal spending in this model? I.e, If we’re patient philanthropists, which choices should we spend money on and which should we save once we factor in that some choices are easier to affect than others? For example, one choice might be particularly hingey under any of your proposed definitions but be very hard for a philanthropist to affect; e.g the decisions made by one person who might not have heard of EA (either as a world leader or just being coincidentally important). We probably won’t get a great payoff from spending a load of money/effort identifying that person and would prefer to avoid that path down the decision tree entirely.
I guess the thrust of the question here is how we might account for tractability of affecting choices in this model. Once tractability is factored in me might prefer to spend a little money affecting lost of small choices which aren’t as hingey under this definition rather than spending a lot affecting one very hingey choice. If this is the case I think we’d want to redefine hingeyness to match our actual decision process.
It seems like each edge on the tree might need a probability or cost rating to fully describe real-world questions of traceability but I’d be very interested in yours or others thoughts.
(Or maybe precipicipality?)