The paper presents the FRIA project aimed at researching and specifying a methodology to assess the impact of Artificial Intelligence (AI) systems on fundamental rights, as recognised by the international and European regulations of hard law and soft law, with the specific reference to the judicial sector as the field of analysis. The research methodology starts from the study of the existing legal and ethical frameworks concerning AI and human rights and the translation of the identified rules and principles into a set of synthetic requirements to create an automated risk assessment methodology. The research output is a prototype tool to support and automate the fundamental rights impact assessment of high-risk AI systems, which is in line with the requirements of the European Artificial Intelligence Act.

Fria implementation model according to the ai act modello di applicazione della fria conforme all’AI Act

Savella R.;Trasarti R.;Pratesi F.
2024

Abstract

The paper presents the FRIA project aimed at researching and specifying a methodology to assess the impact of Artificial Intelligence (AI) systems on fundamental rights, as recognised by the international and European regulations of hard law and soft law, with the specific reference to the judicial sector as the field of analysis. The research methodology starts from the study of the existing legal and ethical frameworks concerning AI and human rights and the translation of the identified rules and principles into a set of synthetic requirements to create an automated risk assessment methodology. The research output is a prototype tool to support and automate the fundamental rights impact assessment of high-risk AI systems, which is in line with the requirements of the European Artificial Intelligence Act.
2024
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
AI Act
ELS
FRIA
High-risk AI systems
Impact assessment
Law&Ethics
Metrics methodology
Risk management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/554928
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