AI Impact Assessment Explainer
An AI impact assessment is a structured process for examining how an AI or automated decision system may affect people and institutions. It begins with the intended use, decision context, affected groups, and potential benefits and harms.
The assessment may examine data quality, privacy, fairness, accessibility, security, explainability, human oversight, appeal routes, and the duration or reversibility of consequences. Higher potential impact usually calls for stronger controls and review.
Completing the assessment early can influence whether the project proceeds and how it is designed. It should be revisited before production and whenever the system’s purpose, users, data, or operating environment changes materially.
An assessment is most useful when it produces actions, owners, deadlines, and evidence. A questionnaire completed only for compliance can miss lived impacts, so engagement with domain experts and affected communities is often necessary.
An AI impact assessment examines how an automated system may affect people, organizations, rights, services, and communities before and during deployment.
Key terms include impact assessment, affected group, consequence, mitigation, oversight, appeal, reversibility, lifecycle and review.
The same model can carry very different consequences in entertainment and public services.
Assessments therefore examine the decision, users, environment, and available recourse.
Identified risks need assigned mitigations, owners, evidence, and follow-up dates.
If the process cannot influence design or deployment, it becomes paperwork rather than risk management.
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