Balancing AI innovation and data privacy: the role of synthetic data and privacy-enhancing technologies in GDPR compliance
Sav, Sultan Damla (A.A. 2023/2024) Balancing AI innovation and data privacy: the role of synthetic data and privacy-enhancing technologies in GDPR compliance. Tesi di Laurea in Data protection law, Luiss Guido Carli, relatore Filiberto Brozzetti, pp. 45. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Literature review. Understanding synthetic data: definitions and data: and compliance implications. Definition and purpose of PETs. GDPR Key principles and limitations for privacy-enhancing technologies. Methodology. Research approach. Data sources and legal frameworks. Analytical framework. Results & discussion. Exploring GDPR and the AI act. Practical benefits and sector-specific applications. Privacy-enhancing technologies: implementation challenges. Privacy-enhancing technologies in practice. Healthcare and financial services: AI, GDPR, and PETs in practice. Bridging AI innovation and data privacy: ethics, governance, and future trends. Bridging the gap between GDPR and AI innovation. Regulatory sandboxes and future compliance strategies.
References
Bibliografia: pp. 41-45.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Digital Innovation and Sustainability (LM/SC – GIUR) |
| Chair: | Data protection law |
| Thesis Supervisor: | Brozzetti, Filiberto |
| Thesis Co-Supervisor: | Catanzariti, Mariavittoria |
| Academic Year: | 2023/2024 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 08 Jul 2025 07:40 |
| Last Modified: | 08 Jul 2025 07:40 |
| URI: | https://tesi.luiss.it/id/eprint/42778 |
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