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> What if machine learning systems come up with results that agree with "evil" stereotypes and "biases"? This is already the case, and shouldn't be surprising.
by j2kun 11y ago
> What if machine learning systems come up with results that agree with "evil" stereotypes and "biases"?
This is already the case, and shouldn't be surprising. That is why the legal system can veto popular opinion, to protect minorities from the prejudice of the majority. The problem is that many people still don't realize that algorithms reinforce popular prejudice and institutionalized bias against the uneducated and the poor.
- yummyfajitas 11y agoIf computer systems are getting the wrong conclusion, that's a boring philosophical question. Find better SVM params/neural network architecture/etc and you'll fix it. But what if the only way to eliminate "institutionalized bias" from the system is to add statistical bias? What happens if "popular prejudice" isn't actually prejudice but merely a useful prior, and one which non-racist [1] machine learning systems faithfully reproduce? [1] I'm using "racist" in the classical sense of f(x.copy(race=A)) != f.copy(x.copy(race=B)), not in the modern sense of "any probabilistic cause for unequal statistical outcomes".