I expect the population of users will have similar propensity to update on most questions. The biggest reason for updating some questions more often is new facts emerging which cause changes of mind. This is a massive confounder here, since questions with ex ante surprising updates seem harder to predict almost by definition.
Yes, it seems like more uncertain and speculative questions with fewer available evidence would have larger swings in beliefs. So it’s possible that updating does help, but not enough to overcome the difficulty of the problems. If this is what happened, the takeaway is that we should more be more skeptical of predictions that are more speculative and more uncertain, which makes sense.
I could see a way for updating to make predictions worse, if there was systematic bias in whether pro or anti proposition evidence is seen, or a bias in how pro or anti evidence is updated on. To pick an extreme example, if someone was trying to evaluate whether the earth was flat, but only considered evidence from flat earth websites, then higher amounts of updating would simply drag them further and further away from the truth. This could also explain why metacalculus is doing worse on AI prediction than other predictions, if there was a bias specifically in this field.
I expect the population of users will have similar propensity to update on most questions. The biggest reason for updating some questions more often is new facts emerging which cause changes of mind. This is a massive confounder here, since questions with ex ante surprising updates seem harder to predict almost by definition.
Yes, it seems like more uncertain and speculative questions with fewer available evidence would have larger swings in beliefs. So it’s possible that updating does help, but not enough to overcome the difficulty of the problems. If this is what happened, the takeaway is that we should more be more skeptical of predictions that are more speculative and more uncertain, which makes sense.
I could see a way for updating to make predictions worse, if there was systematic bias in whether pro or anti proposition evidence is seen, or a bias in how pro or anti evidence is updated on. To pick an extreme example, if someone was trying to evaluate whether the earth was flat, but only considered evidence from flat earth websites, then higher amounts of updating would simply drag them further and further away from the truth. This could also explain why metacalculus is doing worse on AI prediction than other predictions, if there was a bias specifically in this field.