3 ms·

So this idea seems intuitive at first but turns out to be one of the worst things to treat unfairness. There are several reasons for this from both technical a

by dspoka 9y ago

So this idea seems intuitive at first but turns out to be one of the worst things to treat unfairness. There are several reasons for this from both technical and legal perspective. It is incredibly easy to find statistically significant correlations given just a few (more than 7) different views of the data. In general these ml models are not working with less than hundreds or thousands. If the model learned this suppose racial bias, once, you deleting this column is not going to stop it from learning it again, and I believe some research showed that it actually can make the unfairness more severe. from a legal standpoint a company that may or may not be infringing on rights could just say, oh we can't be because we don't have these fields in our data: which makes it harder to monitor and audit wrong doing. most of the methods that I am familiar try to ease the effects of the learned biases as a post-processing step for the model.

bluecalm 9y ago
>>It is incredibly easy to find statistically significant correlations given just a few (more than 7) different views of the data. In general these ml models are not working with less than hundreds or thousands. I would be interested in seeing examples. So far in this thread the arguments were along the lines of: "but then the algorithms punishes poor neighborhood instead of race" but you shouldn't have address in the data either as (I hope) nobody is ok on punishing people for living in bad neighborhood. We should only include data we would like to see in the explanation of the sentencing. "You are not getting parole because you live in a poor neighborhood" is unfair while most people would be ok with: "You are not getting parole because you willingly associated with people who committed crime".
candiodari 9y ago
The necessary result is that you are no longer judged on your crimes, but on your genes. Why ? Because crimes aren't committed by all groups equally ... so you wouldn't expect the risk to be equal. Even for completely practical reasons there are differences. For obvious reasons a 1.4 meter individual is limited risk for armed robbery, to give an extreme example. But there's hundreds to thousands of things like that, that all randomly affect the distribution. The result is that when all put together, things are seriously out of whack. Also I fear the reverse effect. Communities work, to some extent, because of lack of crime. Doing this will necessarily make those neighborhoods with the "victim" genes more violent, more criminal. The result will be improvement of those neighborhoods ? I have to say, I'm VERY skeptical.

by dspoka 9y ago

bluecalm 9y ago

>>It is incredibly easy to find statistically significant correlations given just a few (more than 7) different views of the data. In general these ml models are not working with less than hundreds or thousands. I would be interested in seeing examples. So far in this thread the arguments were along the lines of: "but then the algorithms punishes poor neighborhood instead of race" but you shouldn't have address in the data either as (I hope) nobody is ok on punishing people for living in bad neighborhood. We should only include data we would like to see in the explanation of the sentencing. "You are not getting parole because you live in a poor neighborhood" is unfair while most people would be ok with: "You are not getting parole because you willingly associated with people who committed crime".

candiodari 9y ago

The necessary result is that you are no longer judged on your crimes, but on your genes. Why ? Because crimes aren't committed by all groups equally ... so you wouldn't expect the risk to be equal. Even for completely practical reasons there are differences. For obvious reasons a 1.4 meter individual is limited risk for armed robbery, to give an extreme example. But there's hundreds to thousands of things like that, that all randomly affect the distribution. The result is that when all put together, things are seriously out of whack. Also I fear the reverse effect. Communities work, to some extent, because of lack of crime. Doing this will necessarily make those neighborhoods with the "victim" genes more violent, more criminal. The result will be improvement of those neighborhoods ? I have to say, I'm VERY skeptical.