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[Commlist] New Report: What are the copyright challenges of AI training?
Thu Jul 23 11:30:40 GMT 2026
NEW AI REPORT: What are the copyright challenges of AI training?
The European Audiovisual Observatory has published a major new report on
AI copyright concerns
*Download here*
<https://2b6ai.r.a.d.sendibm1.com/mk/cl/f/sh/7nVU1aA2nfuMSVh5w6x2rkyOshspiVN/g6wxlWAurerk>
Artificial intelligence (AI) is transforming the way content is created,
but how should European copyright law respond to the challenge of
training AI systems in a balanced way? A new IRIS report from the
European Audiovisual Observatory, *Copyright and AI training*
<https://2b6ai.r.a.d.sendibm1.com/mk/cl/f/sh/7nVU1aA2nfwFS2COugBUu7ID34NcSRt/7hhvQ0zLnEWy>,
examines one of the most pressing legal questions facing Europe's
creative industries: how AI systems are trained and what this means for
copyright of the content we are inputting. This brand-new report has
been authored by Diego de la Vega, Senior Legal Analyst in the
Observatory’s Department for Legal Information.
As the use of AI becomes increasingly an integral part of creative
production, this new report explores the legal framework governing the
use of copyrighted works to train AI models, the growing importance of
text and data mining (TDM), the role of user prompts, and the
relationship between AI platforms and their users.
*Chapter One: AI Content Generation in Context – A Copyright Perspective*
Chapter One traces the explosion in AI use since the introduction of the
first popular generative AI tool in 2022. The author charts their impact
across Europe in both creative and business sectors and delves into the
current state of the art. This report explains the technology
implications of GenAI and agentic AI systems in copyright, and why these
innovations present unique copyright issues, particularly when
copyright-protected works are used to train AI models.
Some sensitive sectors are identified, and the author outlines why
copyright has become a central concern for both content creators and
those deploying AI. The landscape is made even more complex by evolving
legal frameworks, including the landmark Council of Europe Framework
Convention on Artificial Intelligence and the new EU Artificial
Intelligence Act, both of which aim to keep pace with technological
progress.
*Chapter Two: The Role of Text and Data Mining (TDM) Exceptions in AI
Training*
Chapter two dives into the heart of the copyright debate: text and data
mining (TDM) processes which are pivotal to AI training processes. The
report examines the European legal provisions that allow for TDM
exceptions, their roots in the Copyright in the Digital Single Market
Directive (CDSMD), and their intricate relationship with national
copyright laws.
This chapter analyses the opt-out mechanisms, transparency obligations,
and persistent doubts as to whether TDM exceptions fully cover the wide
range of AI training activities. The author shows how European, UK, and
other national approaches diverge on matters of licensing, enforcement,
and the balance between rightsholders and developers. Policy
alternatives across the different jurisdictions range from robust rights
reservation frameworks to wide exceptions for commercial and
non-commercial research.
*Chapter Three: Copyright in AI Training and Prompting*
Chapter three explores the technical complexity of AI training and its
consequences for copyright law. It presents real-world cases like the
German GEMA v OpenAI ruling and breaks down the stages of AI model
training where copyright rights are engaged. The chapter also
demystifies "prompting" (the instructions users give to AI systems) and
discusses the legal status of prompts with regard to AI training.
*Chapter Four: Platforms and Users: The Terms of Service*
Chapter four analyses how AI platforms' terms of service distribute
copyright liability between providers and users. The report presents
examples from leading platforms such as Adobe, ChatGPT, Claude, Copilot,
and Midjourney, highlighting the importance of transparency, opt-out
options, and contractual provisions that impact both creators and end-users.
*Chapter Five: Main Takeaways*
The concluding chapter distills the findings: AI technologies are
advancing at a meteoric pace, but the copyright framework in Europe
tries to keep up with this. The training of AI models on copyrighted
data remains contentious, with text and data mining at the centre of
legal uncertainty, and prompting raising new questions about human
authorship and machine-generated works. Enhanced transparency, clarity,
and balance (between access to datasets and the protection of
rightsholder) mark the key priorities for current discussions and future
policymaking.
/*This is a must-read for policymakers, creators, content industry
professionals, legal experts, academic researchers, and anyone
navigating the intersection of technology and copyright. This report
provides insights, detailed comparisons, and a critical map of ongoing
debates. As Europe awaits further guidance from its courts and
legislators, Copyright and AI training is an essential resource for
understanding where we stand, and where we might be heading, on
copyright’s frontier in the age of artificial intelligence. A second
part exploring the copyrightability of the output produced by AI systems
will follow during the second half of 2026. */
/*The European Audiovisual Observatory is part of the Council of Europe
in Strasbourg, France*/.
*Meet our author*
Diego de la Vega
Diego de la Vega is a senior legal analyst in the Observatory’s
Department for Legal Information. He drafts and coordinates publications
within this department and is also involved in organising its events and
conferences. He joined the European Audiovisual Observatory in 2025.
Prior to this, Diego was a practising lawyer specialising in copyright,
intellectual property and audiovisual law.
--
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