| PhD defence: Building normative diversity into algorithmic news recommendations by Sanne Vrijenhoek 1 July 2026 |
| Conference: 2026 Annual Conference of the Society for Economic Research on Copyright Issues 6 & 7 July 2026 |
Latest News
Paddy Leerssen appointed as Assistant Professor in Platform Regulation
IViR is pleased to announce that Paddy Leerssen will become an Assistant Professor in Platform Regulation from September 1st.
Could AI break our news bubbles?
The dangers of AI are often highlighted. But how can we make technology work for us when we follow the news?
In her PhD thesis, Sanne Vrijenhoek examined how technology can strengthen the position of newsrooms. ‘Personalised news recommendations could also help people break out of their bubble.’
New report: A Minimum Age for Social Media: A Legal Exploration
On 18 June 2026 a legal exploration about de possibility of setting a minimum age for social media in the Netherlands was published. This report was written by dr. Paddy Leerssen and prof. dr. Joris van Hoboken.
Upcoming events
2026 Annual Conference of the Society for Economic Research on Copyright Issues
Amsterdam, The Netherlandshttps://www.serci.org/annual_con…Do Not Cross: Protecting Citizens, Preserving Rights
17th EDEN Conference on Data Protection in Law Enforcement
Lisbon, Portugalhttps://www.era.int/event/16th-e…PLSC Europe 2026
Leuven, Belgiumhttps://www.law.kuleuven.be/citi…Latest publications
Who Do Parties Target?: Worldwide Evidence on Political Microtargeting external link
Abstract
This chapter examines how political parties around the world design and implement targeting strategies in their digital campaigns, highlighting both common practices and important differences across contexts. It asks: How prevalent is political microtargeting across the globe, and how does its use vary across countries and parties? To answer this, the chapter draws on a unique dataset of Facebook and Instagram political advertisements placed during 113 national elections in 95 countries between 2020 and 2022, covering more than 54,000 advertisers and 2.5 million ads. The analysis shows that digital targeting has become a near-universal campaign feature, though its specific use reflects institutional, regulatory, and political conditions. Most campaigns employ relatively simple criteria such as location and demographics, rather than the highly sophisticated methods often assumed in public debates. The chapter concludes by discussing implications for research and regulation, stressing the need to link studies of digital campaigning more closely with theories of party competition and democratic accountability.
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political microtargeting
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Bibtex
Private Enforcement of the Digital Services Act (DSA)
Abstract
The Digital Services Act (DSA) represents a significant shift in EU digital regulation, aiming to create a safe, predictable, and trustworthy online environment whilst protecting fundamental rights. While public oversight and co-regulation by the European Commission and national Digital Services Coordinators (DSCs) have already attracted significant attention, this paper considers the underappreciated role of private litigation in enforcing the DSA. It examines a spectrum of DSA provisions – Articles 14, 25 and 35 – that could play a key role in the private enforcement of platform obligations and user rights. We situate these provisions within broader European private law debates, connecting them to principles of procedural autonomy, the effectiveness of EU law, and established doctrines of tort and contract liability. By analysing different DSA obligations across a range of topics, from content moderation to systemic risk management, we aim to identify potential pathways, as well as obstacles, for tech accountability through European courts.
Links
Digital Services Act (DSA), enforcement, Regulation
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Bibtex
GPT-NL respects copyright – cui bono? – Part 2 external link
“Detective Work We Shouldn’t Have to Do”: Practitioner Challenges in Regulatory-Aligned Data Quality in Machine Learning Systems external link
Abstract
Ensuring data quality in machine learning (ML) systems has become increasingly complex as regulatory requirements expand. In the European Union (EU), frameworks such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (AI Act) articulate data quality requirements that closely parallel technical concerns in ML practice, while also extending to legal obligations related to accountability, risk management, and human rights protection. This paper presents a qualitative interview study with EU-based data practitioners working on ML systems in regulated contexts. Through semi-structured interviews, we investigate how practitioners interpret regulatory-aligned data quality, the challenges they encounter, and the support they identify as necessary. Our findings reveal persistent gaps between legal principles and engineering workflows, fragmentation across data pipelines, limitations of existing tools, unclear responsibility boundaries between technical and legal teams, and a tendency towards reactive, audit-driven quality practices. We also identify practitioners’ needs for compliance-aware tooling, clearer governance structures, and promoting a culture of regulatory-aligned data quality.