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Developing Story: Case Studies of Generative AI's Use in Journalism

Natalie Grace Brigham, Chongjiu Gao, Tadayoshi Kohno, Franziska Roesner, Niloofar Mireshghallah

SoLaR Workshop at NeurIPS 2024 · First arXiv submission

Matches conversations in WildChat to published articles from two news agencies, documenting how source material and generated drafts enter journalistic workflows. The study examines input materials, overlap with published text, and publication timing; its cases do not establish prevalence across journalism.

Dataset and scope

An earlier WildChat release containing approximately 650,000 conversations, before the one-million-conversation release.

Selected finding

The authors match 78 conversations to 111 published articles and report a median output-to-publication ROUGE-L overlap of 0.62.

Section 2 identifies the earlier release; Table 1 reports verified matches; Section 3 reports text overlap. Section 5 states that identified sensitive conversations were subsequently removed. Read the source.

Dates and versions

First arXiv version, initially titled Breaking News; the revised title is Developing Story. ArXiv version history.

Cites the arXiv preprint with its original 2024 preprint year. Uses the revised Developing Story title; the paper also appeared at SoLaR 2024.

The annotation describes the linked source version. Consult the paper for its full methods, assumptions, and limitations.

Cite this paper

Natalie Grace Brigham, Chongjiu Gao, Tadayoshi Kohno, Franziska Roesner, Niloofar Mireshghallah. 2024. Developing Story: Case Studies of Generative AI's Use in Journalism. arXiv preprint.

Show BibTeX
@misc{brigham2024developingstory,
  title = {{Developing Story: Case Studies of Generative AI's Use in Journalism}},
  author = {Brigham, Natalie Grace and Gao, Chongjiu and Kohno, Tadayoshi and Roesner, Franziska and Mireshghallah, Niloofar},
  year = {2024},
  doi = {10.48550/arXiv.2406.13706},
  eprint = {2406.13706},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2406.13706}
}

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