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ZENODO
Report . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
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Journalism and generative AI: data, deals and disruption in the news media

Authors: Jones, Bronwyn; Strait, Andrew; Parnell, Brid-Aine; Horzyk, Amanda Maria; Perez, Jorge;

Journalism and generative AI: data, deals and disruption in the news media

Abstract

Findings from an expert workshop exploring the issues arising from AI companies’ use of news as data for training and grounding AI systems. The rapid development and productisation of generative AI, often using news as data for training and grounding models, has prompted the news industry to respond – some with lawsuits, others with data licensing agreements, but all with renewed attention to their position in a shifting media ecosystem. As the UK government considers expanding the text and data mining exception in copyright law and promotes AI adoption and industry in the AI Opportunities Action Plan, there is a need to understand how changes wrought by generative AI are impacting the news media specifically. In November 2024, BRAID (Bridging Responsible AI Divides) and the Ada Lovelace Institute organised an expert workshop, under Chatham House rules, to explore the state of play in news publishing, including pressing challenges, current responses, and emerging safeguards and solutions. We heard from major news publishers, AI and natural language processing experts, lawyers and legal scholars, and copyright experts. The workshop sought to answer three core questions: 1. What is the state of play in news publishing regarding news as data for AI models?2. What concerns does this situation raise for news publishers and society?3. What solutions/safeguards could support news publishers and the sustainable provision of a plurality of public interest news?

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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