On Controlled Change: Generative AI's Impact on Professional Authority in Journalism

TL;DR

This paper explores how Dutch journalists actively manage AI integration in newsrooms through guidelines, experimentation, and critical assessment, aiming to preserve professional authority amidst technological change.

Contribution

It introduces the concept of controlled change as a framework for understanding journalists' proactive strategies in integrating AI while maintaining authority.

Findings

Journalists develop adaptive guidelines for AI use.

Experimentation helps assess AI's role and effectiveness.

Critical evaluation of AI capabilities and limitations is key.

Abstract

Using (generative) artificial intelligence tools and systems in journalism is expected to increase journalists' production rates, transform newsrooms' economic models, and further personalize the audience's news consumption practices. Since its release in 2022, OpenAI's ChatGPT and other large language models have raised the alarms inside news organizations, not only for bringing new challenges to news reporting and fact-checking but also for what these technologies would mean for journalists' professional authority in journalism. This paper examines how journalists in Dutch media manage the integration of AI technologies into their daily routines. Drawing from 13 interviews with editors, journalists, and innovation managers in different news outlets and media companies, we propose the concept of controlled change. as a heuristic to explain how journalists are proactively setting guidelines, experimenting with AI tools, and identifying their limitations and capabilities. Using professional authority as a theoretical framework, we argue that journalists anticipate and integrate AI technologies in a supervised manner and identify three primary mechanisms through which journalists manage this integration: (1) developing adaptive guidelines that align AI use with ethical codes, (2) experimenting with AI technologies to determine their necessity and fit, and (3) critically assessing the capabilities and limitations of AI systems.