I thought that “13% innocent population in jail is wrong” was a premise, and “individual with 13% probability of innocence in jail in wrong” was the conclusion.
Which seems perfectly reasonable to me: if you have an 87% certainty threshold for conviction, it means you’re willing to tolerate up to 13% of convicts being innocent, an unacceptably high number by my lights.
I agree if you mean that the damage from an irrational bias is higher when the stakes are higher, but disagree if you mean that rational marginal certainty levels needed for conviction would be higher for severe crimes. The risks from letting a thief go free (more thefts) seem lower than the risks from letting a murderer go free (more murders) even compared to the damage done to a potential convicted innocent (assuming no death penalty, and also assuming higher conviction rates would actually result in fewer of the real culprits going free, which often does not seem to be the case).
So it sounds like you’re saying we do have the “if”. But are you sure the number is not just unacceptably high because in any realistic example of a 13% innocent population of convicts, many of them would have to have been seen as having substantially greater than 13% chances of innocence? If not for some biasing effect like that, it’s hard for me to see why the moral question would suddenly be clear once it was stated in population frequencies rather than in individual probabilities.
So it sounds like you’re saying we do have the “if”.
Actually, no, because the equivalence of the two formulations is obvious to me.
But it might not be for everyone; it’s well known that many people find thinking in terms of frequencies more intuitive than thinking in terms of bare probabilities. For such people, a statement about probabilities may simply not have any moral force unless and until it is translated into a statement about frequencies.
But are you sure the number is not just unacceptably high because [...] many of them would have to have been seen as having substantially greater than 13% chances of innocence? If not for some biasing effect like that, it’s hard for me to see why the moral question would suddenly be clear once it was stated in population frequencies rather than in individual probabilities.
Well, people’s intuitions about justice aren’t all that consistent, so I don’t think this particular moral question is going to suddenly become clear to all observers no matter how it’s stated. That being said, though, I don’t think we have any particular reason to think that Guede was convicted on unusually shaky evidence, so it seems reasonable—given certain assumptions—to take our estimates of his case as representative of murder cases in general.
A 13% innocence threshold for each particular case won’t give you a 13% innocent prison population (assuming good estimates, which is probably generous in this context), but if we adopt that criterion and Guede’s in the middle of the probability distribution for murder defendants, it seems likely that the resulting population-level incidence would still land on the bad side of 8 or 10%. Which doesn’t look much better.
By the way, I should probably clarify that I don’t think the LW average of 87% probability of guilt for Guede at all means that he should have been acquitted. I attribute the low number to a lack of confidence due to not having delved sufficiently deeply into the case, as per the third point in my earlier comment.
One should only believe that a miscarriage of justice has occurred in his case if one believes that the jury should not have had more than (say) 87% confidence. But in order to believe that one would presumably have to be highly confident in one’s belief about what information the jury had.
I thought that “13% innocent population in jail is wrong” was a premise, and “individual with 13% probability of innocence in jail in wrong” was the conclusion.
Which seems perfectly reasonable to me: if you have an 87% certainty threshold for conviction, it means you’re willing to tolerate up to 13% of convicts being innocent, an unacceptably high number by my lights.
It gets worse—the most severe crimes face the strongest pro-conviction biases.
...which is of course exactly the opposite of how it should work.
I agree if you mean that the damage from an irrational bias is higher when the stakes are higher, but disagree if you mean that rational marginal certainty levels needed for conviction would be higher for severe crimes. The risks from letting a thief go free (more thefts) seem lower than the risks from letting a murderer go free (more murders) even compared to the damage done to a potential convicted innocent (assuming no death penalty, and also assuming higher conviction rates would actually result in fewer of the real culprits going free, which often does not seem to be the case).
So it sounds like you’re saying we do have the “if”. But are you sure the number is not just unacceptably high because in any realistic example of a 13% innocent population of convicts, many of them would have to have been seen as having substantially greater than 13% chances of innocence? If not for some biasing effect like that, it’s hard for me to see why the moral question would suddenly be clear once it was stated in population frequencies rather than in individual probabilities.
Actually, no, because the equivalence of the two formulations is obvious to me.
But it might not be for everyone; it’s well known that many people find thinking in terms of frequencies more intuitive than thinking in terms of bare probabilities. For such people, a statement about probabilities may simply not have any moral force unless and until it is translated into a statement about frequencies.
Well, people’s intuitions about justice aren’t all that consistent, so I don’t think this particular moral question is going to suddenly become clear to all observers no matter how it’s stated. That being said, though, I don’t think we have any particular reason to think that Guede was convicted on unusually shaky evidence, so it seems reasonable—given certain assumptions—to take our estimates of his case as representative of murder cases in general.
A 13% innocence threshold for each particular case won’t give you a 13% innocent prison population (assuming good estimates, which is probably generous in this context), but if we adopt that criterion and Guede’s in the middle of the probability distribution for murder defendants, it seems likely that the resulting population-level incidence would still land on the bad side of 8 or 10%. Which doesn’t look much better.
By the way, I should probably clarify that I don’t think the LW average of 87% probability of guilt for Guede at all means that he should have been acquitted. I attribute the low number to a lack of confidence due to not having delved sufficiently deeply into the case, as per the third point in my earlier comment.
One should only believe that a miscarriage of justice has occurred in his case if one believes that the jury should not have had more than (say) 87% confidence. But in order to believe that one would presumably have to be highly confident in one’s belief about what information the jury had.
I agree, for reasons outlined here. Like you, I’m speaking hypothetically.