The final edition of our #LeADS newsletter is here! 🎉.Take a look at some of the highlights from our journey and discover some of the key moments that shaped the experience of our ESRs.⬇️⬇️⬇️.

📢 The journey may end, but the impact continues. Thanks to all who contributed—partners, ESRs, & our amazing community. Stay tuned as the results live on through open-access publications.

✈️ ESRs gained real-world insights via secondments at top institutions like @intel, @antitrust_it, @GPDP_IT, and more, ensuring their research aligned with industry and policy challenges.

🎥 ESRs didn’t stop there. They recorded insightful videos on their work (available on YouTube) and developed discussion games like ‘Know-IT-All’ and ‘Privacylandia’ to engage the public.

🏛️Highlights included conferences in Brussels, Crete, Toulouse, Kraków, & Pisa; over 150 blog posts; 30+ newsletters; and cutting-edge research disseminated in open-access journals.

Under the leadership of @SantAnnaPisa & Prof. Giovanni Comandé, LeADS showcased the power of interdisciplinary & cross-cultural collaboration. ESRs worked at the crossroads of law & tech, addressing Privacy, Trust, Data Ownership, & Individual Empowerment.

After four years of intensive research, the LeADS project concludes in Dec 2024! With 7 beneficiaries, 7 partners across 9 European countries, & 15 Early Stage Researchers from 13 nations, we’ve tackled the challenges of a data-driven society. Let’s recap! 🧵

Read the full blog post here to explore these ideas further:

🔹 Soumia El Mestari – ESR 15: What AI Is Stealing! Data Privacy Risks in AI. Soumia discusses how AI’s reliance on user data poses privacy risks and offers strategies to mitigate potential leaks.

🔹 Robert Poe – ESR 14: The Perils of Value Alignment. Robert critiques global AI governance for prioritizing moral goals over legal obligations, urging a realistic, justice-focused approach.

🔹 Onntje Hinrichs – ESR 13: Why Your Data Is Not Your Property (And Why You Still Pay with It). Onntje delves into the paradox of data ownership in the EU, explaining how users "pay" for services with their data despite not owning it.

🔹 Aizhan Abdrassulova – ESR 12: Personal Data Ownership: Individuals’ Perspective in the EU. Aizhan investigates data subjects’ expectations around data ownership and proposes ways to improve personal data management.

🔹 Christos Magkos – ESR 11: Personal Health Information Management Systems (PHIMS). Christos examines how PHIMS empower individuals to manage their health data through unified platforms, integrating devices and records.

🔹 Armend Duzha – ESR 10: Extracting Data Value through Data Governance. Armend highlights how AI, blockchain, and federated learning can enhance data governance to extract value while balancing transparency and privacy.

🔹 Xengie Doan – ESR 9: Collective Consent, Risks, and Benefits of DNA Data Sharing. Xengie explores digital tools for collective consent in DNA data sharing, addressing legal-ethical challenges and enhancing usability.

🔹 Fatma Dogan – ESR 8: To Use or Not to Use? Re-using Health Data in AI Development. Fatma examines how health data can be reused for AI innovations in healthcare while safeguarding transparency and personal data rights.

🔹 Barbara Lazarotto – ESR 7: Can Business-To-Government Data Sharing Serve The Public Good?.Barbara analyzes EU regulations on data sharing and explores whether business-to-government data sharing truly benefits the public.

We're thrilled to share Part III of our blog series showcasing insights from Early-Stage Researchers (ESRs) tackling key challenges at the intersection of law, technology, and governance.

These ESRs are pushing the boundaries of interdisciplinary research, addressing real-world challenges at the nexus of law, technology, and governance. 🔗 Check out the blog post here to read the full abstracts!

🔹 Maciej Zuziak – ESR 6: How to Collaboratively Use Statistical Models in a Secure Way. Maciej’s research dives into privacy, federated learning, and data governance, unraveling the complexities of decentralized learning systems. 📊🔒.