Fundamental Rights Impact Assessment for Artificial Intelligence (FRIA)

What is an impact assessment for artificial intelligence?

A Fundamental Rights Impact Assessment (FRIA) for artificial intelligence systems is a methodical process that analyzes how an AI system may affect people and society. It is a tool designed to ensure that the deployment of technology is accompanied by transparency, accountability, and trust.

An AI impact assessment is carried out in order to:

• identify benefits and risks - not only in legal terms, but also for the social environment, business practices, and ethical standards;

• prevent harms such as discrimination, violations of privacy, lack of human oversight, or dependence on algorithmic errors;

• balance the benefits and the downsides throughout the entire lifecycle of the system - from development, through deployment, to its actual use;

• build a framework of trust that facilitates the adoption of new technologies in the public and private sectors by showing users and citizens that the risks have been anticipated and managed.

This makes it both a risk-management tool (for the organizations and institutions deploying AI) and a tool for protecting the public interest (for the citizens whose rights may be affected).

When is an AI impact assessment required?

An impact assessment is not a universal requirement for every artificial intelligence system. It is especially necessary when a technology has the potential to affect fundamental human rights, public services, or vital sectors of the economy.

Under the EU AI Act

In Regulation 2024/1689, better known as the Artificial Intelligence Act or AI Act, the European legislator introduces the obligation to carry out an impact assessment before the deployment of high-risk systems. The core provision is found in Article 27 of the AI Act: "Fundamental rights impact assessment for high-risk AI systems".

The obligation applies to artificial intelligence systems when they are used by:

• Public-law bodies and private entities providing public services, where they deploy high-risk solutions (for example in social-welfare systems, education, employment, or law enforcement). This means that the assessment is mandatory when high-risk systems are used by public administration (state and municipal). The only exception is for systems that are safety components of critical infrastructure.

• Organizations and companies that use AI systems for financial and insurance purposes, such as:

  • assessing creditworthiness or producing credit scores,

  • determining risk and pricing for life insurance and health insurance.

The law emphasizes that the assessment must be carried out before the system is first deployed and updated whenever there is a significant change - for example, a change in how it is used, its scope, or the group of people affected. This ensures that it remains relevant and useful over time.

The results of the assessment should be notified to the market surveillance authorities, which may request additional information or impose conditions on deployment. In certain cases, the authority may decide that reporting is not mandatory, but the assessment itself remains necessary.

Beyond the legal framework

Even when it is not explicitly required by the AI Act, the assessment is a strongly recommended practice.

Companies and institutions that adopt it voluntarily demonstrate a commitment to transparency, ethics, and responsible deployment of technology. This can be decisive in building trust with partners, clients, and citizens.

What does the impact assessment (FRIA) involve?

The impact assessment is a holistic process that brings together legal, technical, and ethical elements. It is not merely a checklist, but a coherent framework that allows organizations to manage risks and ensure the responsible deployment of artificial intelligence. Its main steps are:

1) Describing the system and the context of use

The first step is to clearly define what the artificial intelligence system is, what it will be used for, and in what environment it will operate. This includes:

• the purpose and intended use of the system;

• the processes in which it will be applied (for example, recruitment, financial analysis, the provision of public services);

• the time frames and frequency of use;

• identifying the groups of people who may be affected - clients, employees, citizens, vulnerable groups.

This lays the foundation for the further analysis.

2) Describing the benefits and the impact on fundamental rights

The next stage is two-directional - on one hand, the expected benefits are described (increased efficiency, faster service, lower costs), and on the other, the possible negative effects on rights are analyzed, such as:

• fairness and non-discrimination,

• protection of personal data,

• reliability and transparency of decisions,

• security and safety.

This is where specific risks are examined - for example, the potential for algorithmic discrimination, a lack of human oversight, or the collection of excessive personal data.

3) Measures to prevent and reduce risks

Analysis is meaningless without practical action. That is why the third step includes a set of technical and organizational measures to limit or offset the potential risks:

• technical measures (configuration, reliability testing, system monitoring);

• human oversight (the ability for decisions to be reviewed and confirmed by specialists);

• risk management (internal policies, staff training, incident procedures).

These measures ensure a balance between the benefits of AI and the protection of people.

4) Documentation and periodic review

Finally, everything must be set out systematically in a document that serves as a reference point and as evidence of the measures taken. The assessment, however, is not a static report - it is a "living document" that is updated whenever the system or its application changes.

• Documentation - a clear description of the identified risks and measures.

• Periodic review - regular updates to ensure that the assessment reflects the actual state of affairs.

• Reporting to supervisory authorities, where this is mandatory or necessary for transparency.

Examples and templates

You can find useful examples and templates for impact assessments at the following links:

• Example and guidance for a FRIA from the Government of the Netherlands

• A ready-to-use Excel template developed by the ALIGNER project, funded under Horizon 2020

➡️ Try Praven Intelekt now!