Keyword: Kunstmatige intelligentie
Panel at CPDP 2026: From AI and Quantum to EuroStack and Digital Commons: Which Way to Digital Sovereignty? external link
Abstract
As Big Tech controls most of the digital infrastructure on which everyday practices depend, digital sovereignty has emerged as a countervailing strategy to (re)gain control over data, technologies, and infrastructures, thereby safeguarding autonomy and self-determination in the digital era. The EU’s digital sovereignty agenda emphasises investment in sectors it considers critical, like artificial intelligence and quantum technologies. Industry and civil society also advocate for domestic alternatives to hyperscalers. The various digital sovereignty visions share commonalities; they highlight the need for European-based infrastructures that comply with EU digital rules, but raise similar concerns about underlying dependencies and geopolitical tensions. At the same time, they differ in the futures they imagine, from becoming a global leader to developing open-source solutions. This panel will investigate what digital sovereignty entails nowadays and the different pathways, from private to public digital infrastructures, towards achieving it.
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Artificial intelligence, Digital sovereignty, quantum technologies
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Remuneration for AI Training: A New Source of Income for Journalists?
Abstract
Generative AI systems threaten to usurp the market for human press and media productions. To enable journalists to act as ‘watchdogs’, highlight societal problems, and prompt necessary changes, remuneration rules should offer support for quality journalistic work by humans. In the EU, the rights reservation option following from Article 4(3) of the 2019 Directive on Copyright in the Digital Single Market – now flanked by the provisions of the AI Act – could support a remuneration system focusing on the use of human journalistic content for AI training. While AI training income would benefit media companies that own large repertoires of journalistic work, individual journalists might not receive an appropriate revenue share. This chapter suggests introducing a general output-based payment obligation on all providers and users of generative AI systems involved in media productions: both companies offering generative AI systems and companies using these systems in the media sector. Mandatory collective rights management could ensure payment directly to individual journalists, as in the repartitioning schemes of collecting societies. The remuneration could also finance funds that improve journalists’ working and living conditions. When distributing AI remuneration, social and cultural institutions could prioritise public interest journalism as a countermeasure to AI-generated misinformation and disinformation.
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Artificial intelligence, Journalism, Media law, remuneration
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No News Is Bad News: The Role of Government in News Markets in the Age of Aggregators and AI
Abstract
Welfare economic theory seeks the justification for government intervention in markets, in market failure, and in distributional issues. An analysis of the market failures that exist in a specific industry or market can not only provide justification for government regulation or other kinds of intervention in general, but it can also suggest which type of intervention or regulation is optimal from a welfare economic perspective. This chapter addresses the question of how the emergence of news aggregator platforms and the introduction of generative AI in news production have affected the market failures that constitute the core problem underlying private investment in news production. The focus of the analysis is on the public good character of news and the positive externalities of news production. The question addressed is: Have the consequences of these existing market failures become more prominent or have they been resolved by these developments? Based on this analysis, the chapter discusses how this informs policy concerning these developments.
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Artificial intelligence, Government, Media law
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Enabling contestation: The right to an explanation of judicial AI external link
Abstract
Judges across the world increasingly use various AI-tools in the administration of justice. However, litigants may be unable to contest important pieces of evidence or legal arguments when the functioning and usage of these systems remains unexplained. This dissertation discusses how a right to an explanation could enable litigant contestation of judicial AI. To that end, a comparative overview is provided of the scope, content, and restrictions of this right under due process safeguards, Data Protection Law, and AI Law in the EU, Brazil, and China. Moreover, based on four different theories of procedural justice, the normative reasons why litigant contestation of judicial AI should be enabled are also discussed. This includes analyses of utilitarian, rights-based (including a dignitarian and a Dworkinian approach), and relational approaches to procedural justice. These highlight different values of litigant contestation; it has instrumental value in error correction, and intrinsic value in respecting the dignity of litigants, either as rational autonomous agents or as socio-relational beings. However, it is technically difficult to faithfully explain the internal workings of certain opaque AI-models. Moreover, integrity and safety concerns and the potential violation of trade secrets and business interests of external developers could block the disclosure of explanations. To address these issues, this dissertation argues that judiciaries should adopt certain technical and organizational measures already during the development of judicial AI. This shows that the right to an explanation should not be conceptualized as a mere procedural right, but also as a substantive requirement that safeguards contestation by design.
Artificial intelligence, contestation, digital justice, right to an explanation
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Comparing the right to an explanation of judicial AI by function; studies on the EU, Brazil, and China
Abstract
Courts across the world are increasingly adopting Artificial Intelligence (AI) to automate various tasks. But the opacity of judicial AI systems can hinder the ability of litigants to contest vital pieces of evidence and legal observations. One proposed remedy for the inscrutability of judicial AI has been the right to an explanation. This paper provides a comparative analysis of the scope and contents of a right to an explanation of judicial AI in the European Union (EU), Brazil, and China; three jurisdictions with distinct legal traditions and institutional architectures. We argue that such a right needs to take into account that judicial AI can perform widely different functions. We provide a classification of these functions, ranging from ancillary to impactful tasks. We subsequently compare, by function, how judicial AI would need to be explained under due process standards, Data Protection Law, and AI regulation in the EU, Brazil, and China. We find that due process standards provide a broad normative basis for a derived right to an explanation. However, these standards do not sufficiently clarify the scope and content of such a right. Data Protection Law and AI regulations contain more explicitly formulated rights to an explanation that also apply to certain judicial AI systems. Nevertheless, they often exclude impactful functions of judicial AI from their scope. Within these laws there is also a lack of guidance as to what explainability substantively entails. Ultimately, this patchwork of legal frameworks suggests that the protection of litigant contestation is still incomplete, requiring further legislative and scholarly efforts to substantiate the right to an explanation in the administration of justice.
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Artificial intelligence, contestation, digital justice, explainability, right to an explanation
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Wege zur KI-Grundvergütung für Kreative – Die Verzahnung individueller und kollektiver Vergütungsmodelle download
Abstract
Zur Sicherstellung einer angemessenen Vergütung für die Nutzung urheberrechtlich geschützter Werke zur Entwicklung von generativen KI-Modellen werden sowohl individuelle Lizenzmodelle als auch kollektive Vergütungslösungen vorgeschlagen. Der folgende Beitrag bespricht den Stand der Diskussion und kontrastiert den aktuellen Trend zu individuellen
Lizenzvereinbarungen mit potenziellen Vorzügen kollektiver Ansätze. Eine Beurteilung der verschiedenen Regelungsoptionen im Licht gesellschaftlicher Belange und gesetzgeberischer Zielsetzungen schließt die Diskussion ab.
Artificial intelligence, Copyright
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Europa moet uit het AI-slop: Maar we moeten het niet hebben van de Digitale Omnibusverordening download
Abstract
Terwijl de wereld in razend tempo de AI-revolutie omarmt, worstelt de Europese Unie met de vraag hoe zij haar plek moet opeisen tussen technologische grootmachten als de VS en China. De analyse van Draghi legt pijnlijk bloot hoe ver Europa achterop is geraakt — en hoe regelgeving, ooit een bron van trots, nu vooral als rem wordt gezien. De nieuwe Digitale Omnibusverordening moet daar verandering in brengen, maar laat vooral zien hoe moeilijk het voor Brussel is om een toekomstgerichte visie op AI en data te ontwikkelen.
Artificial intelligence, Digitale Omnibusverordening, Europe
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AI Hype in Journalism: Visibility, Power, and the Politics of Media Narratives
Abstract
Hype is a phenomenon that emerges from a set of practices rooted in the norms and narratives not only of journalism but of digital media and its algorithmic infrastructure more broadly, in the sociopolitical and cultural capital of technical expertise, and in the ambiguous and uncertain promises of a brighter future made by the world’s techno-elite. In this special issue, we explore media hype around AI functions as a pervasive system that is “sunk into and inside of other structures, social arrangements, and technologies” (Star, Citation1999, 381). We pay particular attention to how AI hype is embedded within journalism’s norms and narratives, labor politics, and the rhetoric of the tech industry. As the different articles in this special issue show, understanding AI hype as a systemic phenomenon conveys its power to shape narratives, practices, and regulations across layered systems of actors and networks, as well as its malleability by different stakeholders.
Artificial intelligence, Journalism, Media law