"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

2024-09-18

AI Summary

This study investigates structural challenges in cross-functional collaboration between journalists and AI practitioners within mainstream Chinese news organizations. Drawing on in-depth interviews with 26 professionals and thematic coding analysis, it identifies six core tensions—particularly misaligned objectives, disciplinary language barriers, and ambiguous role boundaries—in goal setting, professional discourse, and responsibility allocation. The study introduces the novel “technical feasibility–journalistic utility” tension framework to systematically characterize localized AI–journalism collaboration. Building on this, it proposes a three-dimensional optimization model encompassing organizational mechanisms, process design, and capacity co-development. Pilot implementations of the recommendations across three media institutions demonstrate practical viability. The findings offer both a theoretical framework and an empirically grounded operational paradigm for human–AI collaboration in journalism.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation
• Web Mining and Content Analysis: Bridging structured and unstructured data
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

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.

Problem

• Cross-functional AI collaboration in news
• Challenges between journalists and AI professionals
• Enhancing AI collaboration strategies in media

Innovation

• AI integration in news workflows
• Cross-functional collaboration strategies
• Interview-based challenges and recommendations