Artificial Intelligence (AI) Bias Audits to Prevent Algorithmic Discrimination
In today’s regulatory environment, a bias audit is more than a compliance exercise — it’s essential evidence that your Artificial Intelligence selection systems are fair, transparent, and defensible. We equip organizations with a detailed understanding of what bias audits must deliver, how to interpret their findings, and how to act on them. Building on foundational law (e.g., NYC Local Law 144) and informed by emerging practices in Colorado, California, DC, New Jersey, and Illinois. We help employers and vendors use AI Bias Audits to measure, monitor and manage data to prevent algorithmic discrimination, and move from generic AI risk management to audit-ready, regulatory-aligned programs that demonstrate fairness and accountability in hiring, procurement, service delivery, community engagement and other high risk AI selection decisions.
Types of AI Bias Audits we provide:
- Employment Bias Audits
- Procurement Bias Audits
- Service Delivery Bias Audits
- Community Engagement Bias Audits
Bias Audit Key Deliverables:
- Develop AI (Artificial intelligence) fairness metrics tables
- Calculate selection/scoring rates by demographic group
- Identify impact ratios (and intersectional breakdowns)
- Evaluate disparities for statistical significance and persistence
- Design a report of recommendations and findings, including an executive summary, results exhibits (tables/figures), disclosure-ready summary stakeholders and public posting