Nondiscrimination law and AI across health care, insurance, employment, credit and housing
There is no single AI-discrimination statute in the US. Existing nondiscrimination law applies sector by sector, and the exam tests whether you can match the right law to the right industry.
Why this matters for the AIGP exam
Bias scenarios are a Domain II staple, and the tested skill is specific: name the regime that governs the sector in the scenario, and know what a bias finding triggers.
The essentials
- Employment. Title VII of the Civil Rights Act, enforced by the EEOC, covers hiring and promotion tools — including disparate-impact claims, where a neutral-seeming tool disadvantages a protected group regardless of intent. NYC's Local Law 144 adds mandatory annual bias audits for automated employment decision tools.
- Credit. The Equal Credit Opportunity Act: no discrimination in lending, and adverse-action notices must give the actual reasons a model denied credit — "the algorithm said so" is not a lawful explanation.
- Housing. The Fair Housing Act reaches tenant-screening and advertising algorithms.
- Insurance and health. State insurance law (Colorado's SB 21-169 is the named example) restricts unfair discrimination from external data and algorithms; in health care, Section 1557 of the ACA covers discriminatory clinical tools.
- Disparate impact is the common thread. Intent is not required; outcomes are what count. And a bias finding obliges an operational response — audit, remediate, monitor — not just a policy update.
What the exam asks
Match sector to statute, recognise disparate impact in a fact pattern, and pick the response a governance programme owes after a finding.
Going deeper
This page is the condensed version. The full topic — with the detail above expanded and practice questions attached — is in the app, inside Domain II. Domain I, a quarter of the course, is free to try first.
Back to the AIGP study guide.
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