Tough Decisions? Supporting System Classification According to the AI Act

Hanif, Hilmy; Constantino Torres, J.E.; Sekwenz, M.T.; van Eeten, M.J.G.; Ubacht, J.; Wagner, Ben; Zhauniarovich, Y.

doi:10.3233/FAIA230987

Tough Decisions? Supporting System Classification According to the AI Act

Title

Tough Decisions? Supporting System Classification According to the AI Act

Author

Hanif, Hilmy (Student TU Delft)
Constantino Torres, J.E. (TU Delft Organisation & Governance)
Sekwenz, M.T. (TU Delft Organisation & Governance)
van Eeten, M.J.G. (TU Delft Organisation & Governance)
Ubacht, J. (TU Delft Information and Communication Technology)
Wagner, Ben (TU Delft Organisation & Governance)
Zhauniarovich, Y. (TU Delft Organisation & Governance)

Contributor

Sileno, Giovanni (editor)
Spanakis, Jerry (editor)
van Dijck, Gijs (editor)

Date

2023

Abstract

The AI Act represents a significant legislative effort by the European Union to govern the use of AI systems according to different risk-related classes, linking varying degrees of compliance obligations to the system's classification. However, it is often critiqued due to the lack of general public comprehension and effectiveness regarding the classification of AI systems to the corresponding risk classes. To mitigate those shortcomings, we propose a Decision-Tree-based framework aimed at increasing robustness, legal compliance and classification clarity with the Regulation. Quantitative evaluation shows that our framework is especially useful to individuals without a legal background, allowing them to improve considerably the accuracy and significantly reduce the time of case classification.

Subject

AI Act
AIA
Artificial Intelligence
Compliance
Risk Classification

To reference this document use:

http://resolver.tudelft.nl/uuid:84b97250-7922-43ea-a874-14ae6454eefe

DOI

https://doi.org/10.3233/FAIA230987

Publisher

IOS Press

ISBN

9781643684727

Source

Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference