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Seems simple to me - test new algorithms and remove controversial variables. If they are better predictors then use that algorithm. Until then, accurate algor
by Vaslo 6y ago
Seems simple to me - test new algorithms and remove controversial variables. If they are better predictors then use that algorithm. Until then, accurate algorithms should be used - whether they determine that Republicans or race X are more likely to do y.
Don’t get me wrong - You have a duty to get the best models possible, and you should try variables that generalize at higher levels - income instead of race) for example and always be testing.
I heard a story about a particular parole board trying to use an algorithm to predict recidivism rates. It often predicted one race more likely to do so. There is some argument that each case should be looked at individually. I agree. But should we avoid addressing the issue if the algorithm is explainable and a good predictor? Instead we should use it to help lower reoffender rates NOT by denying parole but perhaps assigning additional resources to those more likely to offend once we have already granted parole.
- im3w1l 6y agoThe justice system should proportionally reward good behavior and punish bad behavior. It should neither reward nor punish "neutral" behavior. As parole is a part of the punishment it must be determined also according to these criteria. Having inmates trying to guess at what some algorithm values so they can game it? Kafkaesque A bit more leeway can be given to algorithms that companies use but justice system is very sensitive.
- cozzyd 6y agoyeah, if the algorithm is secret, nobody will trust that it's fair if the algorithm is public, it can and will be gamed. The solution is to make the algorithm be based on the things that you want people to game, but that becomes not much of an algorithm at some point...
- aaron-santos 6y agoI think it comes down to this question: should people interacting with a model have the right to know how that model behaves in ways that are socially relevant? In the parole example, should parolees have access to the knowledge that the model predicts different recidivism rates for different races and by how much? In the business world, the answer is reached by answering the question "How would our reputation change if the public had access to this information?" The end result is that AI ethicists are hired for optics and subsequently have no real capacity to publish this information. Is this similar to how we interact with food? Is the 1990 Nutrition Labeling and Education Act a good or bad analogy to use? How similar is this to a food company hiring a food inspector and then firing them when they discover that peanut might have contaminated some other products? I guess if people don't know they won't complain too much.