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.

This paper uncovers the risks inherent in facial recognition within law enforcement, exploring multidimensional aspects affecting data protection vs public security within the regulatory frameworks of the General Data Protection Regulation and the Artificial Intelligence Act.

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.

Public value in the making of automated and datafied welfare futures

Doris Allhutter, Austrian Academy of Sciences
Anila Alushi, University of Leipzig
Rafaela Cavalcanti de Alcântara, Austrian Academy of Sciences
Maris Männiste, Södertörn University
Christian Pentzold, University of Leipzig
Sebastian Sosnowski, Polish Academy of Sciences
PUBLISHED ON: 30 Sep 2024 DOI: 10.14763/2024.3.1803

This article considers the public value of automated and datafied welfare and uses the capability approach, buen vivir, and data justice to explore the relation between the procedural and normative components of emerging infrastructures of welfare.

Introduction to the special issue on AI systems for the public interest AI systems for the public interest

Theresa Züger, Alexander von Humboldt Institute for Internet and Society
Hadi Asghari, Alexander von Humboldt Institute for Internet and Society
PUBLISHED ON: 30 Sep 2024 DOI: 10.14763/2024.3.1802

As the debate on public interest AI is still a young and emerging one, we see this special issue as a way to help establish this field and its community by bringing together interdisciplinary positions and approaches.

The principle of proportionality not only addresses the conflict among competing interests under Article 15(1)(h) GDPR but also shapes the justifications for public interest restrictions on the right of access to AI decision-making information.

The unusual DAO: An ethnography of building trust in “trustless” spaces

Tara Merk, French National Centre for Scientific Research (CNRS)/University of Paris II
PUBLISHED ON: 24 Sep 2024 DOI: 10.14763/2024.3.1795

This paper investigates decentralised autonomous organisations (DAOs) as a potential policy response to the issue of declining trust online and argues that while DAOs have privileged displacing the need for trust, they can also be designed to nourish trust thereby fostering participation and prosocial use cases.

Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies?

Valerie Hase, LMU Munich
Jef Ausloos, University of Amsterdam
Laura Boeschoten, Utrecht University
Nico Pfiffner, University of Zurich
Heleen Janssen, University of Amsterdam
Theo Araujo, University of Amsterdam
Thijs Carrière, Utrecht University
Claes de Vreese, University of Amsterdam
Jörg Haßler, LMU Munich
Felicia Loecherbach, University of Amsterdam
Zoltán Kmetty, Centre for Social Sciences
Judith Möller, University of Hamburg – Leibniz Institute for Media Research (HBI)
Jakob Ohme, Weizenbaum Institute for the Networked Society
Elisabeth Schmidbauer, LMU Munich
Bella Struminskaya, Utrecht University
Damian Trilling, Vrije Universiteit Amsterdam
Kasper Welbers, Vrije Universiteit Amsterdam
Mario Haim, LMU Munich
PUBLISHED ON: 16 Sep 2024 DOI: 10.14763/2024.3.1793

This study critically discusses platforms’ non-compliance with data access based on a collaborative policy effort from scholars engaging in data donation studies.

General-purpose AI regulation and the European Union AI Act

Oskar J. Gstrein, University of Groningen
Noman Haleem, University of Groningen
Andrej Zwitter, University of Groningen
PUBLISHED ON: 1 Aug 2024 DOI: 10.14763/2024.3.1790

This article provides an initial analysis of the EU AI Act's approach to general-purpose artificial intelligence, arguing that the regulation marks a significant shift from reactive to proactive AI governance, while concerns about its enforceability, democratic legitimacy and future-proofing remain.