Algorithmic impact assessment
A structured analysis conducted before and during AI deployment to understand who might be harmed and how, enabling organisations to act before problems occur.
The Simple Version
A structured analysis conducted before and during AI deployment to understand who might be harmed and how, enabling organisations to act before problems occur.
Detailed Explanation
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.
Key Characteristics
- Structured process covering identification, assessment, mitigation, and monitoring
- Related to but broader than GDPR DPIAs and EU AI Act FRIAs
- Increasingly required by sector regulations and public procurement rules
- Should involve affected community engagement for meaningful risk assessment
Why It Matters
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.
Real-World Analogy
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.
Common Misconceptions
- An AIA is only required for public-sector AI, private-sector organisations in regulated sectors face equivalent obligations and good practice expectations.
- An AIA is a one-time pre-deployment exercise, impact assessments should be revisited as systems, data, and deployment contexts evolve.