Frontiers in Public Health 01 frontiersin.org What is the impact of artiﬁcial intelligence-based chatbots on infodemic management? Plinio P. Morita 1,2,3,4,5 *, Matheus Lotto 1,6 , Jasleen Kaur 1 , Dmytro Chumachenko 1,7 , Arlene Oetomo 1 , Kristopher Dylan Espiritu 1 and Irfhana Zakir Hussain 1 1 School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada, 2 Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada, 3 Research Institute for Aging, University of Waterloo, Waterloo, ON, Canada, 4 Centre for Digital Therapeutics, Techna Institute, University Health Network, Toronto, ON, Canada, 5 Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada, 6 Department of Pediatric Dentistry, Orthodontics, and Public Health, Bauru School of Dentistry, University of São Paulo, Bauru, Brazil, 7 Department of Mathematical Modelling and Artiﬁcial Intelligence, National Aerospace University “Kharkiv Aviation Institute”, Kharkiv, Ukraine Artiﬁcial intelligence (AI) chatbots have the potential to revolutionize online health information-seeking behavior by delivering up-to-date information on a wide range of health topics. They generate personalized responses to user queries through their ability to process extensive amounts of text, analyze trends, and generate natural language responses. Chatbots can manage infodemic by debunking online health misinformation on a large scale. Nevertheless, system accuracy remains technically challenging. Chatbots require training on diverse and representative datasets, security to protect against malicious actors, and updates to keep up-to-date on scientiﬁc progress. Therefore, although AI chatbots hold signiﬁcant potential in assisting infodemic management, it is essential to approach their outputs with caution due to their current limitations. KEYWORDS artiﬁcial intelligence, infodemic, health information management, misinformation, eHealth Introduction e widespread availability of Internet access has led to its use as a primary source of health information. Online health information-seeking behavior goes beyond searching for symptoms, diagnoses, and treatments for speciﬁc conditions (1, 2); self-care and healthy lifestyle choices have become increasingly prioritized. Digital resources empower individuals to make informed health decisions and contribute to a more equitable and accessible healthcare landscape (3). Additionally, the vast reservoir of big data stemming from individuals’ online health-seeking behavior also possesses the potential to provide insights for public health decisions (4). Researchers access this big data through public APIs, collaborations with platform providers, or web scraping tools, ensuring that user privacy and anonymity are maintained. Such data becomes foundational in Infodemiology, revealing patterns in health information dissemination and consumption. Infodemiology comes to the fore as a scientiﬁc framework with a core focus on analyzing the dissemination and inﬂuence of information within electronic platforms, particularly on the Internet, and across diverse populations (5). OPEN ACCESS EDITED BY Ulises Cortés, Universitat Politecnica de Catalunya, Spain REVIEWED BY Ricardo Valentim, Federal University of Rio Grande do Norte, Brazil *CORRESPONDENCE Plinio P. Morita plinio.morita@uwaterloo.ca RECEIVED 09 October 2023 ACCEPTED 31 January 2024 PUBLISHED 13 February 2024 CITATION Morita PP, Lotto M, Kaur J, Chumachenko D, Oetomo A, Espiritu KD and Hussain IZ (2024) What is the impact of artiﬁcial intelligence- based chatbots on infodemic management? Front. Public Health 12:1310437. doi: 10.3389/fpubh.2024.1310437 COPYRIGHT © 2024 Morita, Lotto, Kaur, Chumachenko, Oetomo, Espiritu and Hussain. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Perspective PUBLISHED 13 February 2024 DOI 10.3389/fpubh.2024.1310437