The DOI matches its Crossref record.
The European Commission's Proposal for an Artificial Intelligence Act
Open accessAbstract
This chapter presents an analysis of the proposed AI Act as the first general attempt to regulate artificial intelligence in the EU. The article analyses the difficulties of making correct policy choices as well as the details of the EU proposal. Critical assessment of some of the Act's strengths and weaknesses is provided.
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Facial emotion recognition is legally classified as high-risk in school settings under the GDPR and EU AI Act.
“Facial emotion recognition, which relies on sensitive biometric data (e.g., facial expressions), is legally classified as high-risk in school settings under the GDPR and EU AI Act [38]”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [38]
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AI integration in financial services: a systematic review of trends and regulatory challenges
Vukovic, D. B., Dekpo-Adza, S., & Matović, S. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04850-8 · Cited by 216
The place of content ranking algorithms on the AI risk spectrum
Bayer, J. (2024) · Telecommunications Policy · doi:10.1016/j.telpol.2024.102741 · Cited by 9
Why it Remains Challenging to Assess Artificial Intelligence
Brecker, K., Lins, S., & Sunyaev, A. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.641 · Cited by 7
A mesterséges intelligencia jogi szabályozásának aktuális kérdései az Európai Unióban
Kitti, M. (2023) · In Medias Res · doi:10.59851/imr.12.1.4 · Cited by 5
Han, B., Ma, Y., Coghlan, S., McKay, D., Buchanan, G., & Smith, W. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790360 · Cited by 3
AI Innovations in Market Risk Analysis and VaR Modelling
Saravanakrishnan, V., Nandhini, M., & Palanivelu, P. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-6215-0.ch002
Chen, Y. (2026) · Digital Government Research and Practice · doi:10.1145/3807513
Begum, F., & Valan, J. A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0408-1.ch003
Metadata
- Authors
- Ebers, M.
- Corresponding author
- Ebers, Martin
- ORCID
- Ebers, Martin
- Venue
- Research Handbook on EU Internet Law
- Publisher
- Edward Elgar Publishing
- Published
- 2023-10-20
- Pages
- 271-292
- OpenAlex
- W4387934656
- Cited by
- 7
- References
- 0
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 2 · 2023: 2
- FWCI
- 34.19
- Type
- book chapter
- Language
- en
- Open access
- green
- nbn-resolving.org
- Licence
- cc-by
- Locations
- Edward Elgar Publishing eBooks (publishedVersion)
- publish.UP (University of Potsdam) (submittedVersion, cc-by)
- Universität Potsdam (cc-by)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Keywords
- EU AI Act, European Commission, AI regulation, European Union policy, regulatory policy, AI governance
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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