Responsible AI & Bias Assessment
Evaluates whether your AI program actively tests for bias, monitors fairness metrics, includes diverse perspectives in development, and has governance structures to ensure AI outcomes are equitable and transparent.
Why This Assessment
AI systems inherit bias from the data they are trained on, the teams that build them, and the business objectives they are optimized for — organizations that do not actively test for bias are not bias-free, they are bias-blind. The stakes are rising: CFPB guidance on algorithmic credit decisions, EEOC AI hiring guidance, HUD fair housing requirements, and EU AI Act fairness provisions all create enforceable obligations for AI systems that affect real people. This assessment evaluates six dimensions of responsible AI maturity — from bias testing practices to fairness governance — to surface where your organization is most exposed. A high score reflects an AI program that earns trust; a low score is an invitation to build one before a regulator or a headline does it for you.
About your organization
This context shapes your benchmarking and the tone of your recommendations.