I was making in-paradigm critiques, since, if something is internally invalid, it gives us good reason to think it is also externally invalid.
I linked to the XPT tournament just as an example of asking non-experts for predictions. I thought that pandemics were a good example since most people don’t know much about pandemics at all so we should expect their guesses to be very off. I could see the argument that forecasting research has found forecasters to be better than experts so it makes sense to ask non-experts, but it’s important to note that we haven’t validated this over very long time periods.
I linked to the GPI paper since it seems to pretty absurd to me to try to guess how many future there will be. Even if we can come up with accurate estimates for carrying capacity for different regions of space, I have no clue how we could predict the likelihood of reaching carrying capacity in these regions of space.
In regards to your last point, I think my view is most basically that, by assigning probabilities to outcomes, we’re giving ourselves excessive confidence when we often have too little knowledge to warrant the confidence, that correct decision theories should take into account our cluelessness to a much greater extent, and that people probably do Bayesian reasoning a lot worse than they think.
That said, I’m still figuring out my views on decisions theories so I probably should have researched this topic a lot more before making a post.
For your last point, I agree with you that we run into the problem of EV-maxxing being undefined, but I don’t know where to go from there. It doesn’t seem to make sense to me to do anything in regards to something with such a wide probability range because it seems like you’ll just spend all your time chasing things that you know very little about but which suggest really high EV.
I was making in-paradigm critiques, since, if something is internally invalid, it gives us good reason to think it is also externally invalid.
I linked to the XPT tournament just as an example of asking non-experts for predictions. I thought that pandemics were a good example since most people don’t know much about pandemics at all so we should expect their guesses to be very off. I could see the argument that forecasting research has found forecasters to be better than experts so it makes sense to ask non-experts, but it’s important to note that we haven’t validated this over very long time periods.
I linked to the GPI paper since it seems to pretty absurd to me to try to guess how many future there will be. Even if we can come up with accurate estimates for carrying capacity for different regions of space, I have no clue how we could predict the likelihood of reaching carrying capacity in these regions of space.
In regards to your last point, I think my view is most basically that, by assigning probabilities to outcomes, we’re giving ourselves excessive confidence when we often have too little knowledge to warrant the confidence, that correct decision theories should take into account our cluelessness to a much greater extent, and that people probably do Bayesian reasoning a lot worse than they think.
That said, I’m still figuring out my views on decisions theories so I probably should have researched this topic a lot more before making a post.
For your last point, I agree with you that we run into the problem of EV-maxxing being undefined, but I don’t know where to go from there. It doesn’t seem to make sense to me to do anything in regards to something with such a wide probability range because it seems like you’ll just spend all your time chasing things that you know very little about but which suggest really high EV.
Thanks for the thoughtful comment.