Laurens Naudts

According to our database, Laurens Naudts authored at least 8 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Public accountability and regulatory expectations for AI in journalism: qualitative evidence from focus groups with Dutch citizens.

Sophie Morosoli, Laurens Naudts, Hannes Cools, Karthikeya Puttur Venkatraj, Natali Helberger, Claes de Vreese

AI Soc., February, 2026

From Vulnerable Data Subjects to Vulnerabilizing Data Practices: Navigating the Protection Paradox in AI-Based Analyses of Platformized Lives.

Delfina Sol Martinez Pandiani, Ella Streefkerk, Laurens Naudts, Paula Helm

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

Understanding AI Disclosure Needs for News Production and Journalism.

Karthikeya Puttur Venkatraj, Sophie Morosoli, Hannes Cools, Laurens Naudts, Claes de Vreese, Natali Helberger, Pablo César, Abdallah El Ali

Proceedings of the 24th International Conference on Mobile and Ubiquitous Multimedia, 2025

2024

AI-generated journalism: Do the transparency provisions in the AI Act give news readers what they hope for?

Stanislaw Piasecki, Sophie Morosoli, Natali Helberger, Laurens Naudts

Internet Policy Rev., 2024

The Digital Faces of Oppression and Domination: A Relational and Egalitarian Perspective on the Data-driven Society and its Regulation.

Laurens Naudts

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Transparent AI Disclosure Obligations: Who, What, When, Where, Why, How.

Abdallah El Ali, Karthikeya Puttur Venkatraj, Sophie Morosoli, Laurens Naudts, Natali Helberger, Pablo César

Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

2021

Documenting Computer Vision Datasets: An Invitation to Reflexive Data Practices.

Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler, Diana Serbanescu, Alex Hanna

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2019

Tell Me What You Know: GDPR Implications on Designing Transparency and Accountability for News Recommender Systems.

Luciana Monteiro Krebs, Oscar Luis Alvarado Rodriguez, Pierre Dewitte, Jef Ausloos, David Geerts, Laurens Naudts, Katrien Verbert

Proceedings of the Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 2019