Discussion
Where does algorithmic bias usually originate?
Answer: D
Learned systems reproduce whatever regularities exist in their training data, so historical under-representation or discriminatory decisions are learned as patterns. Choice of objective and of features contributes as well. The algorithm's mathematics is neutral between groups, hardware is irrelevant, and deliberate discrimination is rare and a different problem. Locating the origin of a harm correctly determines whether the remedy is better data, a different objective or a constraint on the output.
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