Research articles on GOVERNANCE

Despite their active and growing involvement in monitoring the implementation of the “Code of Conduct on countering illegal hate speech online”, civil society organisations have been barred from translating this expanded role into enhanced influence at the policy-making level.

This article compares the Stop Hate for Profit campaign and the Global Alliance for Responsible Media to evaluate efforts that leverage advertisers’ financial power to challenge platform content moderation.

Framing the role of experts in platform governance: Negotiating the code of practice on disinformation as a case study

Kateryna Chystoforova, European University Institute
Urbano Reviglio, European University Institute
PUBLISHED ON: 31 Mar 2025 DOI: 10.14763/2025.1.1823

This study examines experts' role within the EU's Code of Practice on Disinformation, highlighting challenges in co-regulatory processes and platform governance.

(Un)disclosed brand partnerships: How platform policies and interfaces shape commercial content for influencers

Taylor Annabell, Utrecht University
Laura Aade, University of Luxembourg
Catalina Goanta, Utrecht University
PUBLISHED ON: 15 Nov 2024 DOI: 10.14763/2024.4.1814

This paper analyses how platform policies and interfaces of TikTok, YouTube, Snap, and Instagram shape commercial content for influencers and the legal duty to disclose such content under European consumer law.

Between the cracks: Blind spots in regulating media concentration and platform dependence in the EU

Theresa Josephine Seipp, University of Amsterdam
Natali Helberger, University of Amsterdam
Claes de Vreese, University of Amsterdam
Jef Ausloos, University of Amsterdam
PUBLISHED ON: 14 Nov 2024 DOI: 10.14763/2024.4.1813

The DSA, DMA, and EMFA aim to regulate platform power over digital services and markets while establishing rules to protect media freedom, pluralism, and editorial independence, notably through efforts to address media concentration; however, they seem to overlook some of the underlying causes driving these concentration threats.

Accountability protocols? On-chain dynamics in blockchain governance

Kelsie Nabben, European University Institute
Primavera De Filippi, National Center of Scientific Research (CNRS)
PUBLISHED ON: 8 Oct 2024 DOI: 10.14763/2024.4.1807

This paper focuses on the dynamics of accountability in blockchain governance. Drawing on a case study of the Lido protocol on Ethereum, it explores the rule of code, on-chain accountability, accountability trade-offs, and the complexities of determining when accountability can be better instantiated via on-chain or off-chain mechanisms.

Balancing public interest, fundamental rights, and innovation: The EU’s governance model for non-high-risk AI systems

Michael Gille, Hamburg University of Applied Sciences
Marina Tropmann-Frick, Hamburg University of Applied Sciences
Thorben Schomacker, Hamburg University of Applied Sciences
PUBLISHED ON: 30 Sep 2024 DOI: 10.14763/2024.3.1797

The article takes an in-depth look at the AI Act’s governance approach to non-high-risk AI systems and provides a multi-perspective analysis of the challenges that the EU’s regulation of AI brings about.

Balancing efficiency and public interest: The impact of AI automation on social benefit provision in Brazil

Maria Alejandra Nicolás, Federal University of Latin American Integration
Rafael Cardoso Sampaio, Federal University of Paraná
PUBLISHED ON: 30 Sep 2024 DOI: 10.14763/2024.3.1799

The Brazilian Social Security Management Office's AI system reduces the waiting list but increases automatic refusals, harming beneficiaries and increasing inequality in the delivery of public services to the poorest and elderly people.

Contesting the public interest in AI governance

Tegan Cohen, Queensland University of Technology (QUT)
Nicolas P. Suzor, Queensland University of Technology (QUT)
PUBLISHED ON: 30 Sep 2024 DOI: 10.14763/2024.3.1794

This article explores some conditions and possibilities for public contestability in AI governance; a critical attribute of governance arrangements designed to align AI deployment with the public interest.