Search results
Results: 257
Number of items: 257
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Sax, M., & Helberger, N. (2024). Digital Vulnerability and Manipulation in the Emerging Digital Framework. In N. Helberger, B. Kas, H.-W. Micklitz, M. Namysłowska, L. Naudts, P. Rott, M. Sax, & M. Veale (Eds.), Digital Fairness for Consumers (pp. 10-24). BEUC. https://www.beuc.eu/reports/digital-fairness-consumers -
Naudts, L., Helberger, N., Sax, M., & Veale, M. (2024). Toward Constructive Optimisation: A new perspective on the regulation of recommender systems and the rights of users and society. In N. Helberger, B. Kas, H.-W. Micklitz, M. Namysłowska, L. Naudts, P. Rott, M. Sax, & M. Veale (Eds.), Digital Fairness for Consumers (pp. 25-68). BEUC. https://www.beuc.eu/reports/digital-fairness-consumers -
Micklitz, H.-W., Helberger, N., Kas, B., Namysłowska, M., Naudts, L., Rott, P., Sax, M., & Veale, M. (2024). Towards Digital Fairness. Journal of European Consumer and Market Law, 13(1), 24-30. https://kluwerlawonline.com/journalarticle/Journal+of+European+Consumer+and+Market+Law/13.2/EuCML2024004 -
Piasecki, S., Morosoli, S., Helberger, N., & Naudts, L. (2024). AI-generated journalism: Do the transparency provisions in the AI Act give news readers what they hope for? Internet Policy Review, 13(4). https://doi.org/10.14763/2024.4.1810 -
Helberger, N. (2024). FutureNewsCorp, or how the AI Act changed the future of news. Computer Law & Security Review, 52, Article 105915. https://doi.org/10.1016/j.clsr.2023.105915 -
Dobber, T., Kruikemeier, S., Helberger, N., & Goodman, E. (2024). Shielding citizens? Understanding the impact of political advertisement transparency information. New Media & Society, 26(11), 6715-6735. https://doi.org/10.1177/14614448231157640 -
Helberger, N., Kas, B., Micklitz, H.-W., Namysłowska, M., Naudts, L., Rott, P., Sax, M., & Veale, M. (2024). Digital Fairness for Consumers. BEUC. https://www.beuc.eu/reports/digital-fairness-consumers -
Kieslich, K., Helberger, N., & Diakopoulos, N. (2024). My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts. In ACM FAccT '24: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency : June 3rd-6th 2024, Rio de Janeiro, Brazil (pp. 2071-2085). The Association for Computing Machinery. https://doi.org/10.1145/3630106.3659026
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