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What happens when we train them on an incredibly wide set of randomly-sampled data, which should show no built-in bias, and uncomfortable conclusions emerge? Do
by core-questions 7y ago
What happens when we train them on an incredibly wide set of randomly-sampled data, which should show no built-in bias, and uncomfortable conclusions emerge? Do we censor the AI, castigate someone else in the chain for the problem, or just deal with reality as it presents itself?
- megablast 7y agoIn this example, where would you get the tags for the photos from, if not people who are biased?
- core-questions 7y agoWhy assume that the people are "biased"? If the people are labelling things the way that people generally do, the software will return labels that are useful. Any kind of filtering needed to censor this for people's personal comfort should be implemented on top.