AI use in American newspapers is widespread, uneven, and rarely disclosed
- URL: http://arxiv.org/abs/2510.18774v1
- Date: Tue, 21 Oct 2025 16:22:07 GMT
- Title: AI use in American newspapers is widespread, uneven, and rarely disclosed
- Authors: Jenna Russell, Marzena Karpinska, Destiny Akinode, Katherine Thai, Bradley Emi, Max Spero, Mohit Iyyer,
- Abstract summary: We audit a dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025.<n>Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated.<n>We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles.
- Score: 27.418820851102925
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
Related papers
- Academic journals' AI policies fail to curb the surge in AI-assisted academic writing [0.6800474505694646]
We analyze 5,114 journals and over 5.2 million papers to evaluate the real-world impact of AI usage guidelines.<n>We show that despite 70% of journals adopting AI policies, researchers' use of AI writing tools has increased dramatically across disciplines.<n>Our findings suggest that current policies have largely failed to promote transparency or restrain AI adoption.
arXiv Detail & Related papers (2025-12-07T07:30:53Z) - Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysis [57.68073583427415]
We study whether media coverage has the potential to push AI creators into the production of safe products.<n>Our results reveal that media is indeed able to foster cooperation between creators and users, but not always.<n>By shaping public perception and holding developers accountable, media emerges as a powerful soft regulator.
arXiv Detail & Related papers (2025-09-02T12:13:34Z) - Artificial Intelligence Index Report 2025 [39.08798007138432]
New in this year's report are in-depth analyses of the evolving landscape of AI hardware, novel estimates of inference costs.<n>We also introduce fresh data on corporate adoption of responsible AI practices.<n>The AI Index has been cited in major media outlets such as The New York Times, Bloomberg, and The Guardian.
arXiv Detail & Related papers (2025-04-08T02:01:37Z) - Could AI Trace and Explain the Origins of AI-Generated Images and Text? [53.11173194293537]
AI-generated content is increasingly prevalent in the real world.<n> adversaries might exploit large multimodal models to create images that violate ethical or legal standards.<n>Paper reviewers may misuse large language models to generate reviews without genuine intellectual effort.
arXiv Detail & Related papers (2025-04-05T20:51:54Z) - Almost AI, Almost Human: The Challenge of Detecting AI-Polished Writing [55.2480439325792]
This study systematically evaluations twelve state-of-the-art AI-text detectors using our AI-Polished-Text Evaluation dataset.<n>Our findings reveal that detectors frequently flag even minimally polished text as AI-generated, struggle to differentiate between degrees of AI involvement, and exhibit biases against older and smaller models.
arXiv Detail & Related papers (2025-02-21T18:45:37Z) - Suspected Undeclared Use of Artificial Intelligence in the Academic Literature: An Analysis of the Academ-AI Dataset [0.0]
Academ-AI documents examples of suspected undeclared AI usage in the academic literature.
Undeclared AI seems to appear in journals with higher citation metrics and higher article processing charges.
arXiv Detail & Related papers (2024-11-20T21:29:36Z) - Willingness to Read AI-Generated News Is Not Driven by Their Perceived Quality [3.036383058306671]
This study investigates the perceived quality of AI-assisted and AI-generated versus human-generated news articles.<n>It also investigates whether disclosure of AI's involvement in generating these news articles influences engagement with them.
arXiv Detail & Related papers (2024-09-05T13:12:16Z) - Consent in Crisis: The Rapid Decline of the AI Data Commons [74.68176012363253]
General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data.
We conduct the first, large-scale, longitudinal audit of the consent protocols for the web domains underlying AI training corpora.
arXiv Detail & Related papers (2024-07-20T16:50:18Z) - Artificial Intelligence Index Report 2024 [15.531650534547945]
The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI)
The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on AI.
This year's edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives.
arXiv Detail & Related papers (2024-05-29T20:59:57Z) - Artificial intelligence adoption in the physical sciences, natural
sciences, life sciences, social sciences and the arts and humanities: A
bibliometric analysis of research publications from 1960-2021 [73.06361680847708]
In 1960 14% of 333 research fields were related to AI, but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times.
In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times.
We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.
arXiv Detail & Related papers (2023-06-15T14:08:07Z) - Artificial Intelligence and Life in 2030: The One Hundred Year Study on
Artificial Intelligence [74.2630823914258]
The report examines eight domains of typical urban settings on which AI is likely to have impact over the coming years.
It aims to provide the general public with a scientifically and technologically accurate portrayal of the current state of AI.
The charge for this report was given to the panel by the AI100 Standing Committee, chaired by Barbara Grosz of Harvard University.
arXiv Detail & Related papers (2022-10-31T18:35:36Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.