I think that a model of an individual’s preferences is likely to be better represented by taking multiple approaches, where each fails differently.
I agree. But what counts as a failure? Unless we have a theory of what we’re trying to define, we can’t define failure beyond our own vague intuitions. But once we have a better theory, defining failure becomes a lot easier.
I agree, and think work in the area is valuable, but would still argue that unless we expect a correct and coherent answer, any single approach is going to be less effective than an average of (contradictory, somewhat unclear) different models.
As an analogue, I think that effort into improving individual prediction accuracy and calibration is valuable, but for most estimation questions, I’d bet on an average of 50 untrained idiots over any single superforecaster.
I agree. But what counts as a failure? Unless we have a theory of what we’re trying to define, we can’t define failure beyond our own vague intuitions. But once we have a better theory, defining failure becomes a lot easier.
I agree, and think work in the area is valuable, but would still argue that unless we expect a correct and coherent answer, any single approach is going to be less effective than an average of (contradictory, somewhat unclear) different models.
As an analogue, I think that effort into improving individual prediction accuracy and calibration is valuable, but for most estimation questions, I’d bet on an average of 50 untrained idiots over any single superforecaster.