A structured analysis conducted before and during AI deployment to understand who might be harmed and how — enabling organisations to act before problems occur.
A structured analysis conducted before and during AI deployment to understand who might be harmed and how — enabling organisations to act before problems occur.
Algorithmic impact assessments (AIAs) draw on environmental impact assessment and data protection impact assessment (DPIA) methodologies. They typically cover: system description and intended use, stakeholder mapping and affected population analysis, risk identification across fairness, privacy, safety, and rights dimensions, severity and likelihood assessment, mitigation planning, and monitoring commitments. The EU AI Act's Fundamental Rights Impact Assessment (Article 27) and GDPR's DPIA requirement are closely related specialisations of the broader AIA concept. Canada's Algorithmic Impact Assessment tool and the Canadian Directive on Automated Decision-Making represent early regulatory implementations.
Organisations in the public sector and regulated industries are increasingly required to conduct AIAs before procuring or deploying AI in high-stakes contexts — making this a standard due-diligence step for responsible AI deployment.
Like an Environmental Impact Assessment before a major construction project — a systematic, documented process to identify potential harms before they occur, enabling design changes or safeguards to be implemented proactively.
A structured analysis conducted before and during AI deployment to understand who might be harmed and how — enabling organisations to act before problems occur.
Algorithmic impact assessments (AIAs) draw on environmental impact assessment and data protection impact assessment (DPIA) methodologies. They typically cover: system description and intended use, stakeholder mapping and affected population analysis, risk identification across fairness, privacy, safety, and rights dimensions, severity and likelihood assessment, mitigation planning, and monitoring commitments. The EU AI Act's Fundamental Rights Impact Assessment (Article 27) and GDPR's DPIA requirement are closely related specialisations of the broader AIA concept. Canada's Algorithmic Impact Assessment tool and the Canadian Directive on Automated Decision-Making represent early regulatory implementations.
Organisations in the public sector and regulated industries are increasingly required to conduct AIAs before procuring or deploying AI in high-stakes contexts — making this a standard due-diligence step for responsible AI deployment.