Workshops

The AI Privacy Paradox: Balancing Data Minimization with Large Language Models

Time

TBD

Location

Sánchez Moreno Room (SF 1.141)

About this Session

The workshop, titled “The AI Privacy Paradox: Balancing Data Minimization with Large Language Models,” explores the “legal-technological” paradox arising from the GDPR’s strict requirement for data minimization (which mandates that personal data be used only to the extent strictly necessary) and the AI Act’s comparatively permissive stance. Participants will analyze the practical implications of this divergence, specifically how companies increasingly invoke a “legitimate interest” in technological development to justify opt-out policies that may elude GDPR consent standards. Through a deep dive into the NOYB vs. Meta case, students will examine the tension between massive data harvesting machine learning and individual rights such as access and erasure. The session culminates in an interactive evaluation of the European Commission’s Digital Omnibus and the proposed Article 88c.

The Presenters

Flavia Cuccaro (UNIVAQ)

Flavia Cuccaro is a legal scholar and lawyer specializing in public law and the intersection of technology and governance. She is currently a Doctoral Researcher in Industrial, Information, and Economic Engineering at the University of L’Aquila, where her research focuses on the regulation of Fintech, Artificial Intelligence, and Space Law. She graduated at LUISS Guido Carli University of Rome (Italy) with a degree in Law and Innovation (110/110 cum laude); her academic work, focused on the digital transformation of the European public administrations, has earned special distinction. Lastly, she serves as a Teaching Assistant at LUISS for the following courses: Administrative Law, EU Law, Space Law and Geopolitics, Negotiation, and Law and Tech.

Contact:

www.linkedin.com/in/flaviacuccaro | flavia.cuccaro@graduate.univaq.it

Venue Details

Sánchez Moreno Room (SF 1.141)

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