4 ms·

France does not use any algorithmic decision making in its court system as far as I am aware, but like many people said here, in the end, the cause is not "race

France does not use any algorithmic decision making in its court system as far as I am aware, but like many people said here, in the end, the cause is not "race" itself but the correlations it comes with (e.g: in France, people that commit crimes are more likely to be from poor suburbs, which are predominantly populated by people whose parents came from North Africa/Subsaharan Africa).

bluecalm 9y ago
I am not convinced. Including address sounds like a very bad idea as well. We don't want to punish people for being black just as much as we don't want to punish people for living in poor neighborhoods. It seems to me you should only include data you are ok to make decisions on. This will require collecting more information during court proceeding than you have in general statistics though.
- mc32 9y ago
  But what if geography does have an influence on behavior because incidentally there is a lead-acid battery manufacturer who is a bit lax about dumping, in say a country with less regulation? Or let's say the algorithm is deciding on insurance of some sort's premiums and someone is living next to a SuperFund site.
  - goialoq 9y ago
    Geography is a good place to look for clues to causes, but a not good justification for locking people in jail without trial.
  - bluecalm 9y ago
    >>But what if geography does have an influence on behavior because incidentally there is a lead-acid battery manufacturer who is a bit lax about dumping I don't want to punish people for living in polluted areas therefore I don't include that data in the training set. >>Or let's say the algorithm is deciding on insurance of some sort's premiums and someone is living next to a SuperFund site. I am not ok with doing that therefore I don't include address in the data. Am I ok with punishing people for living in poor/dangerous neighborhood? No? Then don't include that in the data. Am I ok with people paying more for car insurance if they drive in a city with more cars/accidents/worse driving culture? Yes? Then I include it in the data there.
    - mc32 9y ago
      >"Am I ok with punishing people for living in poor/dangerous neighborhood? No? Then don't include that in the data. Am I ok with people paying more for car insurance if they drive in a city with more cars/accidents/worse driving culture? Yes? Then I include it in the data there." I'm not sure I can reconcile that. 1. in the first option, we're not applying the consequences random people, we'd be affecting those already found to have committed a crime. 2. in the second option, if we think we'd be affecting innocent people in option 1. why do we think we would not be affecting innocent people (good drivers who happen to live among poor drivers) in options 2? That's to say, either both are right or both are wrong. I see the same effects in both.

bluecalm 9y ago

I am not convinced. Including address sounds like a very bad idea as well. We don't want to punish people for being black just as much as we don't want to punish people for living in poor neighborhoods. It seems to me you should only include data you are ok to make decisions on. This will require collecting more information during court proceeding than you have in general statistics though.

mc32 9y ago
But what if geography does have an influence on behavior because incidentally there is a lead-acid battery manufacturer who is a bit lax about dumping, in say a country with less regulation? Or let's say the algorithm is deciding on insurance of some sort's premiums and someone is living next to a SuperFund site.
- goialoq 9y ago
  Geography is a good place to look for clues to causes, but a not good justification for locking people in jail without trial.
- bluecalm 9y ago
  >>But what if geography does have an influence on behavior because incidentally there is a lead-acid battery manufacturer who is a bit lax about dumping I don't want to punish people for living in polluted areas therefore I don't include that data in the training set. >>Or let's say the algorithm is deciding on insurance of some sort's premiums and someone is living next to a SuperFund site. I am not ok with doing that therefore I don't include address in the data. Am I ok with punishing people for living in poor/dangerous neighborhood? No? Then don't include that in the data. Am I ok with people paying more for car insurance if they drive in a city with more cars/accidents/worse driving culture? Yes? Then I include it in the data there.
  - mc32 9y ago
    >"Am I ok with punishing people for living in poor/dangerous neighborhood? No? Then don't include that in the data. Am I ok with people paying more for car insurance if they drive in a city with more cars/accidents/worse driving culture? Yes? Then I include it in the data there." I'm not sure I can reconcile that. 1. in the first option, we're not applying the consequences random people, we'd be affecting those already found to have committed a crime. 2. in the second option, if we think we'd be affecting innocent people in option 1. why do we think we would not be affecting innocent people (good drivers who happen to live among poor drivers) in options 2? That's to say, either both are right or both are wrong. I see the same effects in both.