Skill

legalcode-algorithmic-impact-assessment

Conduct comprehensive algorithmic impact assessments (AIAs) for AI systems that make or substantially influence consequential decisions affecting individuals. Covers system classification and purpose documentation, training data and data governance analysis, fairness metrics evaluation (demographic parity / impact ratio, equalized odds, calibration / predictive parity, individual fairness, counterfactual fairness), disparate impact testing across all legally relevant protected classes, proxy feature and protected characteristic inference analysis, bias detection and root cause analysis, transparency and explainability audit (model card completeness, LIME/SHAP/feature importance), human oversight mechanism assessment, appeal and contestation procedure review, and ongoing monitoring framework design. Aligned with EU AI Act (Regulation 2024/1689) Articles 9, 10, 14, 27, and Annex III high-risk system categories; NYC Local Law 144 bias audit requirements for automated employment decision tools; Colorado AI Act (SB 24-205, effective June 30 2026) consequential decision impact assessment obligations; California CPRA Automated Decisionmaking Technology (ADMT) Regulations (effective January 1 2026); NIST AI Risk Management Framework (AI RMF 1.0) MAP and MEASURE functions; IEEE 7003-2024 algorithmic bias considerations; and ISO/IEC TR 24027 bias identification guidance. Integrates EEOC Title VII adverse impact guidance, CFPB ECOA adverse action and less-discriminatory-alternative requirements, FTC Section 5 unfairness doctrine, and Fair Housing Act / Fair Credit Reporting Act overlays. Use when deploying AI systems subject to regulatory transparency or accountability requirements; preparing for EU AI Act Article 27 Fundamental Rights Impact Assessment (FRIA); conducting NYC LL 144 annual bias audits; satisfying Colorado SB 24-205 pre-deployment impact assessment obligations; completing California CPRA ADMT risk assessments; assessing employment, credit, housing, healthcare, insurance, education, or criminal justice automated decision systems for disparate impact; or building an organizational algorithmic impact assessment program. Produces comprehensive AIA reports with fairness metrics scorecards, disparate impact findings, bias root cause analysis, transparency audit, human oversight evaluation, remediation roadmaps, compliance mapping, and Glass Box audit trails suitable for regulatory submission and internal governance.