Algorithmic impact assessments force companies to examine whether their AI tools create discriminatory outcomes, privacy risks, or other harms before putting them into use. Several states and the EU have proposed or enacted requirements for these assessments, especially for high-risk applications in hiring, lending, and criminal justice.
Governments and employers increasingly use AI to sort job applicants, set insurance rates, and flag people for benefits audits. Impact assessments force these organizations to identify who gets hurt before deployment, not after. Without them, communities harmed by biased AI have no recourse.
An algorithmic impact assessment isn't the same as a technical audit. A technical audit checks whether the software runs correctly; an impact assessment examines whether the system's real-world results are fair, accurate, and free of discriminatory patterns — a harder and more contested standard.
Governments and employers increasingly use AI to sort job applicants, set insurance rates, and flag people for benefits audits. Impact assessments force these organizations to identify who gets hurt before deployment, not after. Without them, communities harmed by biased AI have no recourse.
An algorithmic impact assessment isn't the same as a technical audit. A technical audit checks whether the software runs correctly; an impact assessment examines whether the system's real-world results are fair, accurate, and free of discriminatory patterns — a harder and more contested standard.