Re:Algorithmic decision making and the cost of fairness (2017)
by mc32 on Thursday January 25, 2018 @01:52AM
(#16229275)
>"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.
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.