Why it matters
Fairness is regulatory + ethical. Understanding shapes responsible AI.
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The architecture
Definitions: demographic parity (equal rates), equal opportunity (equal true positive), equal odds.
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How it works end to end
Definitions incompatible: can't satisfy all at once.
Choose based on values + context.
Fairness through unawareness: don't use protected attribute (often insufficient).
Mitigation: adversarial debiasing, calibration.