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Pengy7

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The Book of Mormon as well, for those of us raised in a certain cult. Also D&C 132[0] where Joseph Smith has a "Revelation" about taking multiple wives and basically threatens his wife with hell if she doesn't go along with it (she wasn't a huge fan of polygamy).

And I command mine handmaid, Emma Smith, to abide and cleave unto my servant Joseph, and to none else. But if she will not abide this commandment she shall be destroyed, saith the Lord; for I am the Lord thy God, and will destroy her if she abide not in my law.

Turns out he was kind of a dick head.

[0] https://www.lds.org/scriptures/dc-testament/dc/132?lang=eng

If so, even if you don't include gender as a feature itself, your outputs may end up being biased (in the technical sense) by gender.

Part of the problem is people using the same word to mean multiple things. For instance, "bias" has a precise mathematical definition in the context of statistics: https://en.wikipedia.org/wiki/Bias_(statistics) . And this sentence makes no sense with that definition. In fact, with linear models it is mathematically impossible to make a "worse" model (in terms of mean squared error) by including more variables (like gender, age, race, etc...).

you can't be "blind" to race, color, religion, and gender

Also I am not sure that this train of thought actually leads to where we want to go. A perfect model isn't necessarily blind to these features, a perfect model treats everyone as an individual.