Ethical Dimensions of Artificial Intelligence Chatbots Use in Rare Disease Diagnosis: A Scoping Review
DOI:
https://doi.org/10.7202/1126619arKeywords:
artificial intelligence, chatbot, rare disease, diagnosis, ethical issuesLanguage(s):
EnglishAbstract
Introduction: A rare disease is a health condition affecting a small percentage of the population, characterized by its low prevalence and the potential to result in chronic disabilities. Symptoms of these diseases may overlap with those of more prevalent conditions, complicating the diagnostic process. Additionally, many rare diseases are genetically inherited, and their diagnosis often requires specialized medical expertise and advanced diagnostic tools, highlighting the need for targeted approaches in healthcare. Consequently, the integration of artificial intelligence (AI) tools, including chatbots, presents a promising opportunity to support diagnostic processes in healthcare. However, their use raises ethical concerns, particularly related to data privacy, patient confidentiality, and the transparency of AI-driven recommendations. Objective: This study explores the ethical issues arising from the use of AI chatbots in rare disease diagnosis. Method: We conducted a scoping review related to ethical issues raised using chatbots in rare diseases diagnosis, searching databases and reference lists between January 1, 2010, and February 10, 2024. Results: Following screening process, six studies were included in the review. Data were grouped into four themes: 1) trust in AI chatbot; 2) humanization/dehumanization of AI; 3) data security and commercialization; and 4) psychometric considerations. Discussion: AI chatbots hold promise for diagnosing rare diseases, but challenges like data scarcity, diagnostic accuracy, and trust remain. Addressing these issues, particularly through improved data representativeness and enhanced collaboration with healthcare professionals, is crucial for the effective integration of AI in clinical practice. Future research should focus on overcoming these limitations to ensure AI can serve as a reliable decision-support tool in rare disease diagnosis.
References
1. Morris S, Fawcett G, Timoney L, Hughes J. Les dynamiques de l’incapacité : les limitations progressives, récurrentes ou fluctuantes. Statistique Canada; 2019.
2. Veilleux, MP. Rapport du Groupe de travail Québécois sur les maladies rares, ministère de la Santé et des services sociaux. Ministère de la Santé et des services sociaux. 17 Jul 2020.
3. Lambert AOC, Montañez CHT, Martinez MB, Funes-Gallanzi M. A conversational agent for use in the identification of rare diseases. Applications for Future Internet: International Summit. In: Sucar E, Mayora O, Munoz de Cote E, editors. Applications for Future Internet. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Cham: Springer; 2017.
4. Hurvitz N, Azmanov H, Kesler A, Ilan Y. Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases. European Journal of Human Genetics. 2021;29(10):1485-90.
5. Groft SC, Posada M, Taruscio D. Progress, challenges and global approaches to rare diseases. Acta Paediatrica. 2021;110(10): 2711-16.
6. Laumer S, Maier C, Gubler FT. Chatbot acceptance in healthcare: Explaining user adoption of conversational agents for disease diagnosis. In: Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019.
7. Faviez C, Chen X, Garcelon N, et al. Diagnosis support systems for rare diseases: a scoping review. Orphanet Journal of Rare Diseases. 2020;15:94.
8. Hallyburton A. Diagnostic overshadowing: An evolutionary concept analysis on the misattribution of physical symptoms to pre-existing psychological illnesses. International Journal of Mental Health Nursing. 2022;31(6):1360-72.
9. Lavoie-Moore M. Portrait de l’intelligence artificielle en santé au Québec. Proposition pour un modèle d’innovation au profit des services de soin de santé publics. Institut de recherche et d’informations socioéconomiques. 16 Nov 2023.
10. Stark L, Pylyshyn Z. Artificial Intelligence (AI) in Canada. The Canadian Encyclopedia. 6 Feb 2006 (updated 11 Feb 2026).
11. Couture V, Haidar H. Une santé à toute épreuve? Éthique de l’utilisation de l’intelligence artificielle dans le secteur de la santé. Éthique publique. 2023;25(1):17-30.
12. Bourassa Forcier M. Intégration de l’IA en santé au Québec : enjeux légaux. Ethics, Medicine and Public Health. 2020;15:100598.
13. Devillers L. L’IA affective, de nouvelles avenues pour la santé. Relations. 2020(808):25.
14. You Y, Tsai C-H, Li Y, Ma F, Heron C, Gui X. Beyond self-diagnosis: How a chatbot-based symptom checker should respond. ACM Transactions on Computer-Human Interaction. 2023;30(4):64.
15. Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Mental Health. 2017;4(2):e19.
16. Hirsch MC, Ronicke S, Krusche M, Wagner AD. Rare diseases 2030: how augmented AI will support diagnosis and treatment of rare diseases in the future. Annals of the Rheumatic Diseases. 2020;79(6):740-43.
17. Martineau JT, Godin FR. Tour d’horizon des enjeux éthiques liés à l’IA en santé. Éthique publique. 2023;25(1):7978.
18. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1):19-32.
19. Chaudhary A, Kumar V. Rare diseases: a comprehensive literature review and future directions. Journal of Rare Diseases. 2025;4:33.
20. Hallowell N, Badger S, Sauerbrei A, Nellåker C, Kerasidou A. “I don’t think people are ready to trust these algorithms at face value”: trust and the use of machine learning algorithms in the diagnosis of rare disease. BMC Medical Ethics. 2022;23:112.
21. Rapp A, Curti L, Boldi A. The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human-Computer Studies. 2021;151:102630.
22. Pereira J, Díaz Ó. Using health chatbots for behavior change: a mapping study. Journal of Medical Systems. 2019;43(5):135.
23. Germain DP, Gruson D, Malcles M, et al. Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease. Orphanet Journal of Rare Diseases. 2025;20:186.
24. Rallet A, Rochelandet F. La régulation des données personnelles face au web relationnel: une voie sans issue? Réseaux. 2011(3):17-47.
25. Zeitoun JD, Ravaud P. L’intelligence artificielle et le métier de médecin. Les Tribunes de la santé. 2019(2):31-5.
26. WHO. Ethics and governance of artificial intelligence for health: large multi-modal models. World Health Organization; 2024.
27. Vaidyam AN, Wisniewski H, Halamka JD, Kashavan MS, Torous JB. Chatbots and conversational agents in mental health: a review of the psychiatric landscape. Canadian Journal of Psychiatry. 2019;64(7):456-64.
28. Phillips C, Parkinson A, Namsrai T, et al. Time to diagnosis for a rare disease: managing medical uncertainty. A qualitative study. Orphanet Journal of Rare Diseases. 2024;19:297.
29. Hogue T. Researchers develop AI chatbot to diagnose rare diseases. OSU Today. 11 Apr 2025.
30. Jefferies JL, Spencer AK, Lau HA, et al. A new approach to identifying patients with elevated risk for Fabry disease using a machine learning algorithm. Orphanet Journal of Rare Diseases. 2021;16:518.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Alexia Bélisle, Marie-Océane Lavoie, Frédéric Banville, Hazar Haidar
This work is licensed under a Creative Commons Attribution 4.0 International License.
The Canadian Journal of Bioethics applies the Creative Commons Attribution 4.0 International License to all its publications. Authors therefore retain copyright of their publication, e.g., they can reuse their publication, link to it on their home page or institutional website, deposit a PDF in a public repository. However, the authors allow anyone to download, reuse, reprint, distribute, and/or copy their publication, so long as the original authors and source are cited.
_smaller.png){kind=logo}
