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Frequently Asked Questions
What are the main sources of AI bias?
Negative legacy, algorithmic prejudice, and underestimation of the main sources of bias in AI, which were identified by the researchers.
Define an example of data bias.
Data bias can be understood from a scenario in which the AI algorithm puts forward a discriminatory result against a specific group of people.
How can one identify bias in AI?
AI bias can be detected and eliminated by running a range of metrics against the class label (sexual orientation, race, gender, and others) to quantify the members of the class towards which a model shows bias.