I’m pretty sure that the question being answered is “How to find the probability of having a disease if you tested positive for it.” I’m observing people interpreting this to mean “What is the accuracy of the test?” which is not the same thing.
Maybe add a bit to distinguish the two questions?
Assuming there is some way of divining the utility of an individual I think this can be viewed from the lens of a similar problem where you have many agents and you want to combine their utility in some way there is the possibility of just maximizing the average utility vs maximizing the median utility.
The benefits of maximizing the median utility is that the designer is most likely to be part of the median and maybe those that are in the median would have higher utility than those in the average utility maximize world but then this might come at the expense of those who’s utility are in the tails of the distribution.
The benefits of maximizing the average utility is that the benefits are more spread out and you don’t get such a polarizing effect that you would get from median utility. I expect that the result would be a world that is “meh” one that is not particularly great but not bad either.
This is different than CEV in that CEV maximizes non-controversial utilities but is indifferent otherwise.
There have been 3 US presidents where impeachment procedures have taken place against a president. That’s ~7% of US presidents. I think that sets a good prior.
I see, so it’s more of a “Who said it first” kind of tracking rather than a reputation system like loan credit.
That will incentivize useful ideas. Might also weakly incentivize the generation of ideas that contain no information whatsoever (not unlike the library of babel.) I would guess credit-tracking would be a useful tool for a human to gauge where an idea might originate but would probably take some extra components to make it a correct credit-tracker without opening it up to be gamed for some kind of profit (or status/incentive/ect). So I guess I agree with the claim.
Can you explain what you mean by “correct credit-tracking” and “new good ideas”?
Test
My understanding is that neural nets already determine the key features that are important to the decision. The importance of a given feature is represented by the weight on a particular neuron/input-feature.
So no we don’t need every feature. We just need all features relevant to the decision. So some amount of pre-processing can definitely help.