Black Box AI and the Sovereignty of Personal Data: Between GDPR and Digital Ethics
DOI:
https://doi.org/10.18662/eljpa/12.1/258Keywords:
black box, GDPR, AI, protection, personal data, digital ethicsAbstract
The emergence of Black Box artificial intelligence poses fundamental challenges to data protection law, particularly with regard to digital sovereignty and the application of the General Data Protection Regulation (GDPR). These algorithmic systems, defined by their lack of transparency and the inability to explain automated decisions, significantly hinder the exercise of guaranteed rights such as data access, objection, and the right to contest automated decisions. Although the GDPR enshrines the principle of transparency and imposes clear obligations on data controllers, opaque AI systems jeopardize the informational autonomy of individuals. The CJEU ruling in the Nowak case reinforces the right to understand the decision-making logic of AI, but practical implementation remains difficult due to trade secret protections. In this context, an expanded legal framework is necessary—one that integrates explainability requirements and ethical accountability to ensure a balance between innovation and the protection of fundamental rights. Furthermore, the distinction between formal transparency and substantive explainability becomes critical in guaranteeing individuals' effective control over the data and decisions that affect them.
References
Bosoer, L., Cantero Gamito, M., & Rubio-Marin, R. (2023). Non-discrimination and the ai act. Law and Digitalization. Arazandi.
Chaudhary, G. (2024). Unveiling the black box: Bringing algorithmic transparency to AI. Masaryk University Journal of Law and Technology, 18(1), 93-122.
Hoxhaj, O., Halilaj, B., & Harizi, A. (2023). Ethical implications and human rights violations in the age of artificial intelligence. Balkan Social Science Review, 22(22), 153-171. https://doi.org/10.46763/BSSR232222153h
Huang, H. (2025). Hiding in plain sight: Algorithmic transparency and explainability under the GDPR: Legal and technical challenges in applying the GDPR’s provisions on transparency and explainability to algorithmic AI systems. [Master’s Thesis in European Union Law 30 ECTS] pp.22-23.https://uu.diva-portal.org/smash/get/diva2:1941957/FULLTEXT01.pdf
Kharitonova, Y. S. (2023). Legal means of providing the principle of transparency of the Artificial Intelligence. Journal of Digital Technologies and Law, 1(2).
Lubin, A. (2022). Big Brother Watch v. UK (Eur. Ct. HR Grand Chamber). International Legal Materials, 61(4), 605-653. https://doi.org/10.1017/ilm.2022.2
Mbah, G. O. (2024). Data privacy in the era of AI: Navigating regulatory landscapes for global businesses. International Journal of Science and Research Archive, 13(2). https://www.researchgate.net/profile/Geraldine-Mbah/publication/387025413_Data_privacy_in_the_era_of_AI_Navigating_regulatory_landscapes_for_global_businesses/links/675c9d8cebc8f979702cae20/Data-privacy-in-the-era-of-AI-Navigating-regulatory-landscapes-for-global-businesses.pdf
Nisevic, M., Cuypers, A., & De Bruyne, J. (2024, June). Explainable AI: Can the AI Act and the GDPR go out for a date?. In 2024 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE. https://doi.org/10.1109/IJCNN60899.2024.10649994
Nnawuchi, U., George, C., & Kammueller, F. (2024, September). Transparency vs explanation of machine learning algorithms: perspectives from recent legal proceedings. In EPIA Conference on Artificial Intelligence (pp. 270-283). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73497-7_22
Papadimitriou, E. (2023). The right to explanation on the processing of personal data with the use of AI systems. International Journal of Law and Changing World, 2, 43. https://doi.org/10.54934/ijlcw.v2i2.53
Schmahl, S. (2022, September). Digitalisation and International Human Rights Law: Opportunities and Critical Challenges. In Digital Transformations in Public International Law (pp. 135-178). Nomos Verlagsgesellschaft mbH & Co. KG. https://www.nomos-elibrary.de/10.5771/9783748931638-135.pdf
Tzimas, T. (2023). Algorithmic transparency and explainability under EU law. European Public Law, 29(4). https://doi.org/10.54648/euro2023021
Vorras, A., & Mitrou, L. (2021). Unboxing the black box of artificial intelligence: algorithmic transparency and/or a right to functional explainability. In EU Internet Law in the Digital Single Market (pp. 247-264). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-69583-5_10
Yilma, K., (2023). Privacy and the role of international law in the digital age. Oxford University Press
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