Call for Papers:

Trust in Generative AI: Foundations, Drivers, and Implications
Special Issue of the Journal of Broadcasting & Electronic Media (JoBEM)
https://beaweb.org/wp/jobem-trust-in-generative-ai-foundations-drivers-and-implications/

Special Issue Editors:
Jörg Matthes, University of Vienna – joerg.matthes@univie.ac.at
Terry Flew, The University of Sydney – terry.flew@sydney.edu.au
Jingyuan Shi, Hong Kong Baptist University – jolieshi@hkbu.edu.hk

Deadline for submissions: November 15, 2025

SCOPE AND OBJECTIVES

The rapid rise of generative AI—a subset of artificial intelligence capable of creating original text, images, or audiovisual content in response to user prompts—is transforming nearly every aspect of human life. In fields such as journalism, politics, healthcare, education, law, and creative industries, generative AI has already reshaped how people seek and consume information—and it will continue to do so. While it offers unprecedented opportunities, it also poses significant ethical, regulatory, societal, and technological challenges. For instance, AI-generated output can be biased, misleading, or inaccurate, potentially causing widespread disruption or harm. Against this backdrop, trust is a critical factor for the adoption and responsible use of generative AI, particularly in high-stake domains such as healthcare, politics, or law. Ultimately, trust influences how individuals interact with, adopt, and rely on this technology across topics, domains, and contexts.

This special issue seeks original submissions from all areas of the field of communication, exploring the foundations, drivers, and consequences of trust in generative AI. We welcome both theoretical and empirical contributions that shed light on how trust in generative AI is built, maintained, or eroded, as well as the broader societal implications of trust in this increasingly relevant technology. Relevant topics for submission include but are not limited to:

• Conceptualization of trust in generative AI, particularly in comparison to traditional approaches
• Development or refinement of trust measures with respect to generative AI
• Human-AI interaction and trust perception as well as formation
• Transparency as well as explainability as drivers of trust
• Fairness and accountability related to trust
• Misinformation, deepfakes, and the erosion of trust
• Trust-building regulatory frameworks

SUBMISSION GUIDELINES

All submissions to the special issue will be subject to a double-blind peer review process. The deadline for submissions is November 15, 2025. Authors should read the instructions for authors prior to submission:

https://www.tandfonline.com/toc/hbem20/current

Papers should be submitted on the journal’s website. Submissions via email will not be accepted. When submitting the paper via the submission portal, please make sure to indicate it as a “Trust in Generative AI” article. Please contact the special issue editors for further clarification. We look forward to receiving your contributions!

ABOUT THE JOURNAL

The Journal of Broadcasting & Electronic Media (JoBEMl) is the scholarly journal published quarterly by the Broadcast Education Association. Considered one of the leading publications in the Communication field, the Journal contains timely articles about new developments, trends and research in electronic media written by academicians, researchers and other electronic media professionals. For more information please visit https://beaweb.org/wp/jobem/