@inproceedings{84b97250792243eaa87414ae6454eefe,
title = "Tough Decisions? Supporting System Classification According to the AI Act",
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.",
keywords = "AI Act, AIA, Artificial Intelligence, Compliance, Risk Classification",
author = "Hilmy Hanif and Jorge Constantino and Sekwenz, {Marie Therese} and {Van Eeten}, Michel and Jolien Ubacht and Ben Wagner and Yury Zhauniarovich",
year = "2023",
doi = "10.3233/FAIA230987",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "353--358",
editor = "Giovanni Sileno and Jerry Spanakis and {van Dijck}, Gijs",
booktitle = "Legal Knowledge and Information Systems - JURIX 2023",
address = "Netherlands",
note = "36th International Conference on Legal Knowledge and Information Systems, JURIX 2023 ; Conference date: 18-12-2023 Through 20-12-2023",
}