Envisioning the Applications and Implications of Generative AI for News Media
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Abstract (arXiv)
This article considers the increasing use of algorithmic decision-support systems and synthetic media in the newsroom, and explores how generative models can help reporters and editors across a range of tasks from the conception of a news story to its distribution. Specifically, we draw from a taxonomy of tasks associated with news production, and discuss where generative models could appropriately support reporters, the journalistic and ethical values that must be preserved within these interactions, and the resulting implications for design contributions in this area in the future. Our essay is relevant to practitioners and researchers as they consider using generative AI systems to support different tasks and workflows.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Feb 2024.
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Citing papers per year: 2024: 5; 2025: 4; 2026: 2.
11 papers.
- 2024Bias Amplification: Large Language Models as Increasingly Biased Mediacited by 12
- 2025"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalismcited by 10
- 2024Quantifying Generative Media Bias with a Corpus of Real-world and Generated News Articlescited by 9
- 2024LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Contentcited by 6
- 2024AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Modelscited by 3
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applicationscited by 3
- 2026More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Productioncited by 3
- 2025Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Makingcited by 2
- 2025Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systemscited by 0
- 2025Towards Real-World Validity in Generative AI Benchmarks: Understanding and Designing Domain-Centered Evaluations for Journalism Practitionerscited by 0
- 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathycited by 0
- 2026LLMs Should Incorporate Explicit Mechanisms for Human Empathy12 Apr 2026
- 2026More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Production16 Jan 2026
- 2025Towards Real-World Validity in Generative AI Benchmarks: Understanding and Designing Domain-Centered Evaluations for Journalism Practitioners30 Sep 2025
- 2025Unmasking Synthetic Realities in Generative AI: A Comprehensive Review of Adversarially Robust Deepfake Detection Systems24 Jul 2025
- 2025"Ownership, Not Just Happy Talk": Co-Designing a Participatory Large Language Model for Journalism28 Jan 2025
- 2025Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Making24 Jan 2025
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applications28 Oct 2024
- 2024LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content20 Oct 2024
- 2024Bias Amplification: Large Language Models as Increasingly Biased Media19 Oct 2024
- 2024AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models10 Oct 2024
- 2024Quantifying Generative Media Bias with a Corpus of Real-world and Generated News Articles16 Jun 2024