Artificial Intelligence, Misinformation, and Libraries: A New Frontier for Information Professionals
Resource type
Author/contributor
- Salubi, Oghenere (Author)
Title
Artificial Intelligence, Misinformation, and Libraries: A New Frontier for Information Professionals
Abstract
Generative artificial intelligence (AI) has experienced rapid advancement, fundamentally transforming the information landscape. This technological shift has not only amplified the dissemination of misinformation but has also posed significant challenges to conventional frameworks of trust and verification. This paper explores the dual impact of AI: its potential to enhance information services while simultaneously amplifying misinformation and disinformation. Seven AI-generated misinformation cases between 2022 and 2025—ranging from deepfakes and political propaganda to impersonation and amplification were analyzed. Through thematic case analysis and interdisciplinary synthesis, the study proposes the AI-Misinformation Resilience Model (AIM-RM), a conceptual framework guiding proactive responses across verification infrastructure, digital literacy, and ethical policy engagement. Drawing on recent scholarly literature and grounded in information ethics, epistemic trust, and sociocultural literacy, the model offers a path forward for LIS professionals seeking to navigate the post-truth era. Annual Meeting of the Association for Information Science & Technology | Nov. 14 – 18, 2025 | Washington, DC, USA.
Publication
Proceedings of the Association for Information Science and Technology
Publisher
John Wiley and Sons Inc
Date
2025
Volume
62
Issue
1
Pages
572-581
Journal Abbr
Proceedings of the Association for Information Science and Technology
Citation Key
salubiArtificialIntelligenceMisinformation2025
ISSN
2373-9231
Short Title
Artificial Intelligence, Misinformation, and Libraries
Language
English
Library Catalog
Scopus
Citation
Salubi, O. (2025). Artificial Intelligence, Misinformation, and Libraries: A New Frontier for Information Professionals. Proceedings of the Association for Information Science and Technology, 62(1), 572–581. https://doi.org/10.1002/pra2.1279
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