Impact assessments for AI

Impact assessments for AI are formal evaluations conducted to identify, analyze, and manage the potential effects of an AI system before or during its use. These assessments focus on understanding how an AI system could influence individuals, communities, or environments, both positively and negatively.

Impact assessments for AI matter because they help organizations avoid legal risks, reduce unintended harm, and build trust with users. They are a crucial part of AI governance frameworks, making sure systems align with ethical principles, human rights standards, and regulatory requirements.

“Only 23% of organizations using AI conduct formal impact assessments before deploying their models.”(Source: World Economic Forum Global AI Survey 2023)

What an AI impact assessment covers

An AI impact assessment examines many aspects of a system’s design, operation, and outcomes. It goes beyond technical performance to explore social, ethical, and legal impacts.

Key focus areas include:

• Privacy risks: How personal data is collected, processed, and protected.

• Bias and discrimination: How the system could favor or harm different groups.

• Transparency: How understandable the system is to users and auditors.

• Accountability: Who is responsible for outcomes and errors.

• Security risks: How vulnerabilities could lead to harm or misuse.

Assessments may be required by law, such as under the [EU AI Act](https://artificialintelligenceact.eu/), or strongly recommended by international standards like ISO/IEC 42001.

Real-world examples of AI impact assessments

The City of Amsterdam and the City of Helsinki created public AI registers, documenting the purpose, risks, and decision-making processes behind municipal AI systems. These registers act as living impact assessments, helping residents understand how AI is used in public services.

Another example comes from healthcare. Before introducing an AI tool for cancer diagnosis, a hospital conducted an impact assessment that included bias testing, patient data privacy review, and a consultation with a bioethics board. This step helped reduce misdiagnosis risks and improved patient trust.

Best practices for conducting AI impact assessments

Conducting strong impact assessments requires a clear process and cross-functional collaboration. Assume a multidisciplinary team is involved early, including legal, technical, and domain experts.

Recommended practices include:

• Start during system design: Do not wait until launch. Identify risks and mitigation plans from the beginning.

• Use structured templates: Follow established models like the Canadian Algorithmic Impact Assessment or the OECD AI Risk Checklist.

• Consult affected stakeholders: Involve communities that might be impacted, especially in sensitive domains like healthcare or justice.

• Document mitigation plans: Clearly outline how risks will be managed or reduced.

• Review and update regularly: Impact assessments should not be one-time reports. They need periodic updates as the AI system evolves.

This approach builds stronger accountability and allows risks to be managed before they escalate into serious issues.

Key questions for an AI impact assessment

FAQ

When is an AI impact assessment required?

An AI impact assessment is usually required when an AI system affects human rights, safety, or significant societal processes. Regulations like the EU AI Act define contexts where it is mandatory.

Who should lead an AI impact assessment?

A neutral team including legal, compliance, ethics, and technical experts should lead the assessment. Product teams should be deeply involved, but assessments should not be controlled by them alone.

What happens if no impact assessment is conducted?

Failure to conduct an impact assessment can lead to legal penalties, reputational damage, and greater risk of harm to users. Organizations might also be banned from using certain AI systems under specific regulations.

Are impact assessments public documents?

Some organizations publish summaries to build public trust. Sensitive parts, such as proprietary technical details or specific vulnerabilities, are often kept confidential.

How often should impact assessments be reviewed?

Impact assessments should be reviewed whenever there is a major update to the AI system, a change in its use, or after a significant incident related to its operation.

Summary

Impact assessments for AI are a key part of responsible AI use. They help identify risks early, protect individuals and communities, and meet legal and ethical obligations. Organizations that invest in thorough impact assessments reduce their exposure to harm and improve trust in their AI systems. Strong governance begins with asking the right questions before AI systems are released into the real world.