Research articles on GOVERNANCE

The extraterritorial application of GDPR does not promote European values. Rather, it evokes wrong expectations about the universality of individual rights.

This paper is part of Governing “European values” inside data flows, a special issue of Internet Policy Review guest-edited by Kristina Irion, Mira Burri, Ans Kolk, Stefania Milan. Introduction Governments’ interest in the “datafied society” (Hintz et al., 2018) as an object of policy and regulation is nothing new, with a long-held recognition that governance protocols (policies, ethics frameworks, and regulations) can be used to reshape the technological infrastructure underpinning society and hence its nature (Floridi, 2018; van Dijck & Poell, 2016). However, the widespread adoption of the term “sovereignty”—a concept loaded with legal and political connotations—to describe authority over …

In this article, I propose a distinction between individual harm, collective harm and societal harm caused by artificial intelligence (AI), and focus particularly on the latter. By listing examples and identifying concerns, I provide a conceptualisation of AI’s societal harm so as to better enable its identification and mitigation. Drawing on an analogy with environmental law, which also aims to protect an interest affecting society at large, I propose governance mechanisms that EU policymakers should consider to counter AI’s societal harm.

This article considers the unique challenges of platform policies aimed at the off-platform misbehaviour of users through the case of Twitch.

How have app stores governed the global app response to the coronavirus pandemic? An exploratory systematic mapping of COVID-19 pandemic response apps.

The spread of hate speech and disinformation on social media has contributed to inflaming conflicts and mass atrocities as seen in Myanmar. Is the doctrine of information intervention a solution to escalations of violence?

This research investigates EU member states’ preferences and coalitions in recent negotiations of the Council of the EU related to the digital single market.

The design of modern machine learning systems should take into account not only their effectiveness in solving a given problem, but also their impact on the rights of individuals. Implementing this goal may involve applying technical solutions proven in the IT industry, such as event logs or certification frameworks.

Recommendation algorithms potentially amplifying extremist content has become a policy concern in recent years. We conduct a novel empirical experiment on three platforms (YouTube, Reddit, and Gab) to test this phenomenon. We find that YouTube’s “Recommended for you” system does promote extreme content. We synthesise the findings into the policy debate and argue that co-regulation may provide some solutions.

The CJEU judgements in the ‘Uber’ and ‘Airbnb’ cases may help to determine whether platform operators bear liability towards platform customers and on what grounds.