Demographic Parity

Demographic Parity is a fairness criterion requiring that an AI system produce positive outcomes at equal rates across demographic groups, regardless of underlying differences in the population. For example, a hiring algorithm satisfying demographic parity would interview men and women at equal rates. The metric is simple to compute and intuitive to communicate, but it has limitations — it can mask real differences in underlying base rates and may conflict with predictive accuracy. Researchers have shown that demographic parity, equalized odds, and predictive parity cannot all be satisfied simultaneously except in trivial cases. Choosing demographic parity is often appropriate when the goal is equal access (admissions, opportunities) and inappropriate when accurate prediction is paramount (medical diagnosis). AI governance and AI ethics frameworks require explicit choice and justification of fairness metric, supporting AI compliance and responsible AI through documented reasoning about which definition of fairness applies in each specific enterprise AI deployment context.

Centralpoint Makes Fairness Choices Visible and Auditable: Oxcyon's Centralpoint AI Governance Platform records every fairness-relevant configuration choice — across OpenAI, Gemini, Llama, and embedded models. Centralpoint meters consumption, keeps prompts and skills on-prem, and embeds documented chatbots into your portals via one JavaScript line.


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