Equalized Odds
A fairness criterion requiring that an AI model's true positive rate and false positive rate are equal across protected groups, ensuring consistent error patterns regardless of demographic category.
In plain language
A fairness check that asks: does the AI make the same types of mistakes equally across groups? It shouldn't be more likely to wrongly flag one group while giving another group a free pass.
Why this matters
This metric is particularly important for high-stakes AI decisions in areas like lending, hiring and insurance. Governance frameworks should specify when equalized odds is the appropriate fairness standard and how it will be measured.
Relevance
GovernanceEqualized odds is a technical fairness control appropriate for systems where both false positives and false negatives carry serious consequences; regulators increasingly expect organisations to define and measure fairness standards.
Related terms
Putting equalized odds into practice in your organisation?
Ready to transform your AI strategy?
Partner with Australia's AI strategy and governance specialists. From adoption roadmaps to ISO 42001 audit readiness.