"It Might be Technically Impressive, But It's Practically Useless to us": Motivations, Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News Industry

Qing Xiao, Xianzhe Fan, Felix M. Simon, Bingbing Zhang, Motahhare Eslami
9/18/2024
cs.HCcs.CYcs.LG

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Abstract

Recently, an increasing number of news organizations have integrated artificial intelligence (AI) into their workflows, leading to a further influx of AI technologists and data workers into the news industry. This has initiated cross-functional collaborations between these professionals and journalists. Although prior research has explored the impact of AI-related roles entering the news industry, there is a lack of studies on how internal cross-functional collaboration around AI unfolds between AI professionals and journalists within the news industry. Through interviews with 17 journalists, six AI technologists, and three AI workers with cross-functional experience from leading Chinese news organizations, we investigate the practices, challenges, and opportunities for internal cross-functional collaboration around AI in news industry. We first study how these journalists and AI professionals perceive existing internal cross-collaboration strategies. We explore the challenges of cross-functional collaboration and provide recommendations for enhancing future cross-functional collaboration around AI in the news industry.

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Cite this paper

@article{xiao2024might,
  title  = {"It Might be Technically Impressive, But It's Practically Useless to us": Motivations, Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News Industry},
  author = {Qing Xiao and Xianzhe Fan and Felix M. Simon and Bingbing Zhang and Motahhare Eslami},
  year   = {2024},
  eprint = {2409.12000},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.12000v2}
}

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