Bias Audit

A Bias Audit is a systematic review of an AI system for discriminatory outcomes across demographic groups, often required by law, contract, or organizational AI policy. New York City Local Law 144, effective 2023, requires annual bias audits of automated employment-decision tools used in NYC by independent auditors. Other regulations imposing audit requirements include Illinois' Artificial Intelligence Video Interview Act and emerging provisions in the EU AI Act. A thorough bias audit examines training data, model architecture, predictions across protected groups, and disparate impact ratios — and produces a written report documenting methodology, findings, and recommendations. Independent third-party audits are increasingly preferred over internal-only audits for credibility. AI governance frameworks treat bias audits as recurring activities, not one-time checks. Strong AI compliance and AI risk management programs schedule periodic audits and respond to findings with documented remediation, supporting responsible AI in any regulated enterprise AI deployment context.

Centralpoint Generates the Audit Evidence Regulators Demand: Oxcyon's Centralpoint AI Governance Platform captures every AI interaction across OpenAI, Gemini, Llama, and embedded models — making bias audits dramatically faster. Centralpoint meters consumption, keeps prompts and skills on-prem, and embeds audit-ready chatbots into your portals with a single line of JavaScript.


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