What do you understand by AI bias? Give 3 examples.
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Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process.
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Researchers have identified three categories of bias in AI: algorithmic prejudice, negative legacy, and underestimation. Algorithmic prejudice occurs when there is a statistical dependence between protected features and other information used to make a decision.
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