AI fairness

A property of an AI system whereby its outputs satisfy a defined criterion of equitable treatment across specified groups — common criteria include demographic parity, equalised odds, equal opportunity, and calibration parity — recognising that these criteria are often mutually incompatible.

ByCASRAI Editorial Board

· Last updated 21 May 2026

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Fairness is not a single property but a family of mutually exclusive mathematical definitions; the choice among them is a value judgement that should be disclosed. Reports of AI use in research that bears on people should state which fairness criterion (if any) was evaluated and the results.

References

Barocas, Hardt, Narayanan 2023 ‘Fairness and Machine Learning’ (textbook)
Chouldechova 2017 ‘Fair Prediction with Disparate Impact’ Big Data

Use in your systems

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