An algorithmic impact assessment is a documented process for identifying how an automated or AI-enabled system could affect people, rights, services, organizations, and the environment before and during use. The result should determine proportionate review, mitigation, transparency, and oversight.
A good AIA moves the review from generic model quality to the real-world consequences of a specific use in a specific context.
Primary authority anchors the definition. Research links add conceptual or operational depth. External sources may update independently; always verify legal duties against the current official text.
A public 106-question tool that maps assessed impact levels to required mitigations.
An influential accountability framework for public-sector automated decision systems.