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Qualifying and Quantifying Risk Under the EU AI Act

Gasiola, Gustavo Gil ORCID iD icon 1; Cen, Sarah; Zufall, Frederike ORCID iD icon 1
1 Fakultät für Informatik (INFORMATIK), Karlsruher Institut für Technologie (KIT)

Abstract:

The EU AI Act uses a risk-based approach to regulate AI systems, calibrating the intensity of regulation according to the risks they pose. While the term 'risk' implies quantification, resulting from the combination of the probability and severity of harm, the AI Act refers to risks to fundamental rights, thereby engaging a qualitative perspective. In this piece, we address this puzzle using a two-step framework under which the EU AI Act balances risks with the protection of fundamental rights, the legitimate purposes of providers and deployers, and the impacts of regulatory measures on providers, deployers, and regulators. We discuss this framework against the backdrop of potential approaches to quantifying risks, with a specific focus on defining and measuring the main components of the concept of risk: probability, severity, and their combination. We suggest that the protection of fundamental rights and risk quantification can be aligned by incorporating quantification methodologies into the proposed framework. In particular, the AI Act implies a balancing analysis that uses a severity-first approach to classify and quantify the risks posed by AI systems. ... mehr


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Originalveröffentlichung
DOI: 10.1609/aies.v9i2.43202
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 3065-8365
KITopen-ID: 1000197920
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in Proceedings of the Ninth AAAI/ACM Conference on AI, Ethics, and Society
Band 9
Heft 2
Seiten 1012–1021
Bemerkung zur Veröffentlichung Proceedings of the Ninth AAAI/ACM Conference on AI, Ethics, and Society (AIES2026)
Vorab online veröffentlicht am 11.10.2026
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