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

arXiv: https://arxiv.org/abs/2510.19792 · HTML: https://mlsanity.com/paper/2510.19792/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 76 references that are in the map.
- First posted on arXiv 22 Oct 2025.

## Builds on (most cited first, 9 of 9)

- [Human heuristics for AI-generated language are flawed](https://mlsanity.com/paper/2206.07271/) (2022)
- [Generating Representative Headlines for News Stories](https://mlsanity.com/paper/2001.09386/) (2020)
- [Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods](https://mlsanity.com/paper/2203.05227/) (2022)
- [Template-free Data-to-Text Generation of Finnish Sports News](https://mlsanity.com/paper/1910.01863/) (2019)
- [Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media](https://mlsanity.com/paper/2405.04706/) (2024)
- [CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation](https://mlsanity.com/paper/2203.16763/) (2022)
- [Code-Switching Detection with Data-Augmented Acoustic and Language Models](https://mlsanity.com/paper/1808.00521/) (2018)
- [A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect](https://mlsanity.com/paper/2105.03409/) (2021)
- [The Impact of Knowledge Silos on Responsible AI Practices in Journalism](https://mlsanity.com/paper/2410.01138/) (2024)

## Built on by (most cited first, 1 of 1)

- [The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election](https://mlsanity.com/paper/2608.10773/) (2026)

## Abstract (arXiv)

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.