Bias: prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair.
If a data set is flawed, it should be fixed, but when ML finds objective patterns our culture finds subjectively unpalatable and we choose to "fix" them, we fall prey to and re-enact the same grade of self-delusion exhibited by, for example, "the church" in the dark ages. Computer science is already low in terms of accountability & rigor compared to other fields without these kinds of suggestions.
If a data set is flawed, it should be fixed, but when ML finds objective patterns our culture finds subjectively unpalatable and we choose to "fix" them, we fall prey to and re-enact the same grade of self-delusion exhibited by, for example, "the church" in the dark ages. Computer science is already low in terms of accountability & rigor compared to other fields without these kinds of suggestions.