Generative AI, Copyright and the AI Act external link

Computer Law & Security Review, vol. 56, num: 106107, 2025

Abstract

This paper provides a critical analysis of the Artificial Intelligence (AI) Act's implications for the European Union (EU) copyright acquis, aiming to clarify the complex relationship between AI regulation and copyright law while identifying areas of legal ambiguity and gaps that may influence future policymaking. The discussion begins with an overview of fundamental copyright concerns related to generative AI, focusing on issues that arise during the input, model, and output stages, and how these concerns intersect with the text and data mining (TDM) exceptions under the Copyright in the Digital Single Market Directive (CDSMD). The paper then explores the AI Act's structure and key definitions relevant to copyright law. The core analysis addresses the AI Act's impact on copyright, including the role of TDM in AI model training, the copyright obligations imposed by the Act, requirements for respecting copyright law—particularly TDM opt-outs—and the extraterritorial implications of these provisions. It also examines transparency obligations, compliance mechanisms, and the enforcement framework. The paper further critiques the current regime's inadequacies, particularly concerning the fair remuneration of creators, and evaluates potential improvements such as collective licensing and bargaining. It also assesses legislative reform proposals, such as statutory licensing and AI output levies, and concludes with reflections on future directions for integrating AI governance with copyright protection.

AI Act, Content moderation, Copyright, DSA, Generative AI, text and data mining, Transparency

Bibtex

Article{nokey, title = {Generative AI, Copyright and the AI Act}, author = {Quintais, J.}, url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4912701}, doi = {https://doi.org/10.1016/j.clsr.2025.106107}, year = {2025}, date = {2025-01-30}, journal = {Computer Law & Security Review}, volume = {56}, number = {106107}, pages = {}, abstract = {This paper provides a critical analysis of the Artificial Intelligence (AI) Act\'s implications for the European Union (EU) copyright acquis, aiming to clarify the complex relationship between AI regulation and copyright law while identifying areas of legal ambiguity and gaps that may influence future policymaking. The discussion begins with an overview of fundamental copyright concerns related to generative AI, focusing on issues that arise during the input, model, and output stages, and how these concerns intersect with the text and data mining (TDM) exceptions under the Copyright in the Digital Single Market Directive (CDSMD). The paper then explores the AI Act\'s structure and key definitions relevant to copyright law. The core analysis addresses the AI Act\'s impact on copyright, including the role of TDM in AI model training, the copyright obligations imposed by the Act, requirements for respecting copyright law—particularly TDM opt-outs—and the extraterritorial implications of these provisions. It also examines transparency obligations, compliance mechanisms, and the enforcement framework. The paper further critiques the current regime\'s inadequacies, particularly concerning the fair remuneration of creators, and evaluates potential improvements such as collective licensing and bargaining. It also assesses legislative reform proposals, such as statutory licensing and AI output levies, and concludes with reflections on future directions for integrating AI governance with copyright protection.}, keywords = {AI Act, Content moderation, Copyright, DSA, Generative AI, text and data mining, Transparency}, }

Anticipating impacts: using large‑scale scenario‑writing to explore diverse implications of generative AI in the news environment

Kieslich, K., Diakopoulos, N. & Helberger, N.
AI and Ethics, 2024

Abstract

The tremendous rise of generative AI has reached every part of society—including the news environment. There are many concerns about the individual and societal impact of the increasing use of generative AI, including issues such as disinformation and misinformation, discrimination, and the promotion of social tensions. However, research on anticipating the impact of generative AI is still in its infancy and mostly limited to the views of technology developers and/or researchers. In this paper, we aim to broaden the perspective and capture the expectations of three stakeholder groups (news consumers; technology developers; content creators) about the potential negative impacts of generative AI, as well as mitigation strategies to address these. Methodologically, we apply scenario-writing and use participatory foresight in the context of a survey (n=119) to delve into cognitively diverse imaginations of the future. We qualitatively analyze the scenarios using thematic analysis to systematically map potential impacts of generative AI on the news environment, potential mitigation strategies, and the role of stakeholders in causing and mitigating these impacts. In addition, we measure respondents' opinions on a specifc mitigation strategy, namely transparency obligations as suggested in Article 52 of the draft EU AI Act. We compare the results across diferent stakeholder groups and elaborate on diferent expected impacts across these groups. We conclude by discussing the usefulness of scenario-writing and participatory foresight as a toolbox for generative AI impact assessment.

Generative AI

Bibtex

article{nokey, title = {Anticipating impacts: using large‑scale scenario‑writing to explore diverse implications of generative AI in the news environment}, author = {Kieslich, K. and Diakopoulos, N. and Helberger, N.}, doi = {https://doi.org/10.1007/s43681-024-00497-4}, year = {2024}, date = {2024-05-27}, journal = {AI and Ethics}, abstract = {The tremendous rise of generative AI has reached every part of society—including the news environment. There are many concerns about the individual and societal impact of the increasing use of generative AI, including issues such as disinformation and misinformation, discrimination, and the promotion of social tensions. However, research on anticipating the impact of generative AI is still in its infancy and mostly limited to the views of technology developers and/or researchers. In this paper, we aim to broaden the perspective and capture the expectations of three stakeholder groups (news consumers; technology developers; content creators) about the potential negative impacts of generative AI, as well as mitigation strategies to address these. Methodologically, we apply scenario-writing and use participatory foresight in the context of a survey (n=119) to delve into cognitively diverse imaginations of the future. We qualitatively analyze the scenarios using thematic analysis to systematically map potential impacts of generative AI on the news environment, potential mitigation strategies, and the role of stakeholders in causing and mitigating these impacts. In addition, we measure respondents\' opinions on a specifc mitigation strategy, namely transparency obligations as suggested in Article 52 of the draft EU AI Act. We compare the results across diferent stakeholder groups and elaborate on diferent expected impacts across these groups. We conclude by discussing the usefulness of scenario-writing and participatory foresight as a toolbox for generative AI impact assessment.}, keywords = {Generative AI}, }