"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

TL;DR

This paper investigates how AI professionals and journalists in Chinese news organizations collaborate internally, highlighting current practices, challenges, and opportunities to improve cross-functional teamwork around AI integration.

Contribution

It provides empirical insights into internal cross-functional collaboration practices and challenges between AI technologists and journalists in the news industry.

Findings

Identifies key perceptions of collaboration strategies

Highlights challenges faced in cross-functional teamwork

Offers recommendations for improving collaboration

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.