How to Reduce Bias in Artificial Intelligence

How to reduce bias in artificial intelligence.


  • How to Reduce Bias in Artificial Intelligence

    Srishti Chaudhary

    Srishti is a competent content writer and marketer with expertise in niches like cloud tech, big data, web development, and digital marketing. She looks forward to grow her tech knowledge and skills.

Frequently Asked Questions

Negative legacy, algorithmic prejudice, and underestimation of the main sources of bias in AI, which were identified by the researchers.

Data bias can be understood from a scenario in which the AI algorithm puts forward a discriminatory result against a specific group of people.

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.

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