I was having trouble understanding the first example of EEV, until I read this part of Will Crouch’s original comment:
We tend to assume, in the absence of other
information, that charities are average at implementing their
intervention, whereas you seem to assume that charities are bad at
implementing their intervention, until you have been shown concrete
evidence that they are not bad at implementing their intervention.
I agree this is wrong. They failed to consider that charities that are above average will tend to make information available showing that they are above average, so absence of information in this case is Bayesian evidence that a charity is below average. Relevant LW post: http://lesswrong.com/lw/ih/absence_of_evidence_is_evidence_of_absence/
What you say is true, but even after taking into account the point about absence of evidence being evidence of absence one still needs to Bayesian adjust on account of measurement errors giving rise to some charities’ activities being overvalued and others being undervalued according to the measurements.
I was having trouble understanding the first example of EEV, until I read this part of Will Crouch’s original comment:
I agree this is wrong. They failed to consider that charities that are above average will tend to make information available showing that they are above average, so absence of information in this case is Bayesian evidence that a charity is below average. Relevant LW post: http://lesswrong.com/lw/ih/absence_of_evidence_is_evidence_of_absence/
What you say is true, but even after taking into account the point about absence of evidence being evidence of absence one still needs to Bayesian adjust on account of measurement errors giving rise to some charities’ activities being overvalued and others being undervalued according to the measurements.