The Transparency Dilemma: An Experiment on How AI Disclosures Affect Credibility Perceptions and Engagement Across Topics

The media sector's credibility has been under significant scrutiny due to a rise in misinformation and the advent of generative AI (Artificial Intelligence) technologies, which pose a further threat to its credibility. Amid these challenges, transparency about the use of AI has been championed as a key solution to restore and promote credibility. Research reveals mixed reactions regarding the transparency of AI-generated content. While some studies indicate that AI-written news might be perceived as more credible than its human-produced counterparts, others find that content labelled as AI impacts credibility negatively. This study clarifies the impact of AI labels on individuals' credibility perceptions by examining the influence of different news topics. Does the usage of AI transparency labels invoke more concern about news credibility in the context of political news compared to non-political news? The effectiveness of transparency cues may be different when it concerns more serious issues, such as political news, versus less important non-political news, such as culture. We conducted a 2x2 survey experiment (N= 207) to investigate the impact of AI disclosures in the context of political news on individuals’ perceptions of source credibility, perceived manipulation, and sharing intentions. Overall, AI as a news source is considered less credible, no matter the topic, yet the AI label does not increase feelings of manipulation. When it comes to sharing intention, this is negatively affected by the AI label, but only in the case of political news. These findings can help news organisations and policymakers to develop meaningful transparency labels.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2025-10-15
DOI
https://doi.org/10.1609/aies.v8i2.36671
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Transparency Dilemma: An Experiment on How AI Disclosures Affect Credibility Perceptions and Engagement Across Topics

Emma van der Goot, Sophie Morosoli, Claes H. de Vreese, Valeria Reséndez et al.
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Misinformation and Its Impacts
article

The Transparency Dilemma: An Experiment on How AI Disclosures Affect Credibility Perceptions and Engagement Across Topics

Emma van der Goot, Sophie Morosoli, Claes H. de Vreese, Valeria Reséndez, Natali Helberger
article en

Abstract

The media sector's credibility has been under significant scrutiny due to a rise in misinformation and the advent of generative AI (Artificial Intelligence) technologies, which pose a further threat to its credibility. Amid these challenges, transparency about the use of AI has been championed as a key solution to restore and promote credibility. Research reveals mixed reactions regarding the transparency of AI-generated content. While some studies indicate that AI-written news might be perceived as more credible than its human-produced counterparts, others find that content labelled as AI impacts credibility negatively. This study clarifies the impact of AI labels on individuals' credibility perceptions by examining the influence of different news topics. Does the usage of AI transparency labels invoke more concern about news credibility in the context of political news compared to non-political news? The effectiveness of transparency cues may be different when it concerns more serious issues, such as political news, versus less important non-political news, such as culture. We conducted a 2x2 survey experiment (N= 207) to investigate the impact of AI disclosures in the context of political news on individuals’ perceptions of source credibility, perceived manipulation, and sharing intentions. Overall, AI as a news source is considered less credible, no matter the topic, yet the AI label does not increase feelings of manipulation. When it comes to sharing intention, this is negatively affected by the AI label, but only in the case of political news. These findings can help news organisations and policymakers to develop meaningful transparency labels.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 8(2)
University of Amsterdam (NL), University of Twente (NL)
Openalex Percentile: Top 61%
Misinformation and Its Impacts
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.