“Journalism Will Always Need Journalists.” The Perceived Impact of AI on Journalism Authority in Switzerland

The increasing adoption of generative AI in news media presents new challenges to journalism, particularly during an era marked by disinformation, audience disaffection, and mistrust towards news media and journalists. The proliferation of voices in news discourse, especially with the rise of social media platforms, has further questioned journalism’s authority, which is defined as the socially constructed right to be listened to [Carlson, 2017. Journalistic authority: Legitimating news in the digital era. Columbia University Press]. This paper examines the integration of AI in Swiss news media through focus groups and semi-structured interviews with 16 media professionals from various newsrooms across the country. The research aims to understand journalists’ perceptions of AI’s impact on journalism’s authority and to identify strategies for ensuring the responsible use of AI without undermining this authority. Findings indicate that a pluralistic governance approach, emphasizing guidelines and human oversight, is crucial for the responsible implementation of AI in the editorial process. Additionally, maintaining emotional agency in news gathering and storytelling is identified as a key strategy for journalists to reaffirm their authority amidst the growing presence of AI in newsrooms.

Authors

Institutions

Publication Details

Journal
Journalism Practice
Published
2025-04-20
DOI
https://doi.org/10.1080/17512786.2025.2487534
Citations
7
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
27.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

“Journalism Will Always Need Journalists.” The Perceived Impact of AI on Journalism Authority in Switzerland

Colin Porlezza, Laura Amigo
7 citations
Journalism Practice
Social Media and Politics
27.05
article

“Journalism Will Always Need Journalists.” The Perceived Impact of AI on Journalism Authority in Switzerland

Colin Porlezza, Laura Amigo
article en
7 citations

Abstract

The increasing adoption of generative AI in news media presents new challenges to journalism, particularly during an era marked by disinformation, audience disaffection, and mistrust towards news media and journalists. The proliferation of voices in news discourse, especially with the rise of social media platforms, has further questioned journalism’s authority, which is defined as the socially constructed right to be listened to [Carlson, 2017. Journalistic authority: Legitimating news in the digital era. Columbia University Press]. This paper examines the integration of AI in Swiss news media through focus groups and semi-structured interviews with 16 media professionals from various newsrooms across the country. The research aims to understand journalists’ perceptions of AI’s impact on journalism’s authority and to identify strategies for ensuring the responsible use of AI without undermining this authority. Findings indicate that a pluralistic governance approach, emphasizing guidelines and human oversight, is crucial for the responsible implementation of AI in the editorial process. Additionally, maintaining emotional agency in news gathering and storytelling is identified as a key strategy for journalists to reaffirm their authority amidst the growing presence of AI in newsrooms.

Journalism PracticeVol. 19(10)
National Institute of Statistics and Geography (MX), Universidad de Londres (MX), Università della Svizzera italiana (CH)
Openalex Percentile: Top 0%
Social Media and Politics
27.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.