Free browser tool; JavaScript required. Use PALO FRIA to organize evidence about how an AI use case may affect fundamental rights. Record the deployment context, affected people, mitigation and review decisions. See what a useful assessment record contains.
What is FRIA and How to Use This Tool
Click to expand the guide
What is FRIA?
A Fundamental Rights Impact Assessment (FRIA) is an Article 27 assessment for certain deployers of high-risk AI systems under Article 6(2). It helps identify how an AI system may affect the fundamental rights protected by the EU Charter in its specific deployment context.
- Public authorities deploying in-scope high-risk AI
- Private entities providing public services
- Deployers of in-scope creditworthiness and life or health insurance risk systems
- Other organizations using this tool voluntarily as a readiness assessment
How to Use This Tool
- Step 1 - Context: Enter AI system details and classification
- Step 2 - Checklist: Answer governance and compliance questions
- Step 3 - Scenarios: Identify potential negative impact scenarios
- Step 4 - Assessment: Rate severity and likelihood of each impact
- Step 5 - Mitigation: Document risk mitigation measures
- Step 6 - Decision: Make deployment decision and generate report
AI System Context
Provide information about the AI system being assessed.
Context Analysis Checklist
Answer these questions about your AI system's governance, data, and oversight.
Impact Scenarios
Identify up to 5 scenarios where the AI system could negatively affect fundamental rights.
Severity & Likelihood Assessment
Assess the severity and likelihood of each identified impact.
Mitigation Measures
Document existing and planned measures to mitigate identified risks.
Deployment Decision
Review your assessment and make a deployment decision.
Build a reviewable fundamental-rights impact record
A useful fundamental-rights impact assessment connects a defined use case to affected people, plausible harms, safeguards and accountable decisions. Completing a checklist alone does not demonstrate that risks are adequately controlled.
What to prepare
- The intended purpose, deployment setting, responsible organization and people affected.
- The evidence supporting each impact judgment, including uncertainty and information still missing.
- Mitigation owners, human oversight, routes for raising concerns and conditions for reassessment.
- A dated record of decisions and the reasons for accepting, changing or stopping the planned use.
Example: an AI-supported service decision
Map the decision path from data collection to human review and the outcome experienced by the individual. Consider who may be excluded, how errors can be challenged and whether the reviewer can meaningfully change the outcome. Keep the assessment tied to the actual deployment rather than a generic model description.
Does PALO determine whether Article 27 applies?
PALO supports preliminary readiness and voluntary governance work. Determine the applicable duties from the current official sources, actor role and deployment context with the responsible reviewer. The tool is not a legal opinion or certification.
Try a completed fictional FRIA record
A public-service triage example records an affected group, two rights, illustrative impact ratings, missing evidence, mitigation owners and a decision to halt deployment. It uses synthetic information and leaves legal classification unresolved.
Download the worked FRIA JSON. Save your current work first, then use Import to inspect the example across all six steps. Explore governance registers.