Algorithmic Impact Assessment (AIA)
A systematic process to evaluate the potential impacts of deploying an algorithmic system on individuals, groups, and society. It identifies risks before deployment and maps out mitigation strategies, serving as both a compliance tool and a design checkpoint.
Why It Matters
AIAs catch problems before they reach production. A discriminatory hiring algorithm or a biased credit model costs far more to fix after deployment — in both dollars and trust — than during design.
Example
Before launching an AI-powered resume screening tool, a company conducts an AIA that tests for demographic bias, evaluates impact on disabled applicants, and documents the appeal process for rejected candidates.
Think of it like...
An AIA is like an environmental impact study for technology — before you build the highway, you figure out what's in the path and how to minimize the damage.
Related Terms
Data Protection Impact Assessment (DPIA)
A systematic assessment of the potential impact of data processing activities on the rights and freedoms of individuals. Required under GDPR for high-risk processing, a DPIA is particularly relevant for AI systems that process personal data at scale or make automated decisions about people.
Fundamental Rights Impact Assessment (FRIA)
An assessment required under the EU AI Act for deployers of high-risk AI systems that evaluates the system's impact on fundamental rights — including non-discrimination, privacy, freedom of expression, and human dignity — before deployment begins.
AI Risk Register
A documented inventory of identified AI risks, their likelihood, severity, mitigation measures, and responsible owners. It serves as a living document that tracks risk across the AI portfolio and informs governance decisions about resource allocation and priority.