Algorithmic Impact Assessment
Systematic evaluation of the potential impacts of an algorithmic system on individuals, groups, and society before and during deployment.
Algorithmic Impact Assessments systematically evaluate AI risks for individuals and society – required by the EU AI Act for high-risk AI.
Explanation
Analogous to Data Protection Impact Assessments (DPIA). Checks: Which groups are affected? What risks exist (discrimination, privacy, autonomy)? What mitigation measures exist? Canada was the first country to introduce a mandatory AIA for government AI.
Marketing Relevance
EU AI Act requires impact assessments for high-risk AI. Proactive AIAs reduce legal risk and build stakeholder trust.
Common Pitfalls
AIAs as bureaucracy instead of real risk analysis. Missing involvement of affected groups. Created once and never updated.
Origin & History
Canada's Directive on Automated Decision-Making (2019) introduced the first mandatory AIA. EU AI Act (2024) formalized Fundamental Rights Impact Assessments. Raji et al. (2020) proposed internal audit frameworks for companies.
Comparisons & Differences
Algorithmic Impact Assessment vs. AI Audit
AIA is prospective (before deployment); AI Audit is retrospective (examines existing systems).
Algorithmic Impact Assessment vs. DPIA (Datenschutz-Folgenabschätzung)
DPIA focuses on data protection risks; AIA covers broader risks (fairness, autonomy, societal impacts).