دورية أكاديمية
أعرض في EDS

Advocating for population health: The role of public health practitioners in the age of artificial intelligence.

التفاصيل البيبلوغرافية
العنوان: Advocating for population health: The role of public health practitioners in the age of artificial intelligence.
المؤلفون: Kamyabi A; Vancouver Coastal Health, Vancouver, BC, Canada., Iyamu I; British Columbia Centre for Disease Control, Vancouver, BC, Canada.; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada., Saini M; Vancouver Coastal Health, Vancouver, BC, Canada., May C; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada., McKee G; British Columbia Centre for Disease Control, Vancouver, BC, Canada.; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada., Choi A; Vancouver Coastal Health, Vancouver, BC, Canada. alexandra.choi1@vch.ca.
المصدر: Canadian journal of public health = Revue canadienne de sante publique [Can J Public Health] 2024 Jun; Vol. 115 (3), pp. 473-476. Date of Electronic Publication: 2024 Apr 16.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 0372714 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1920-7476 (Electronic) Linking ISSN: 00084263 NLM ISO Abbreviation: Can J Public Health Subsets: MEDLINE
أسماء مطبوعة: Publication: Switzerland : Springer Nature
Original Publication: Ottawa : Canadian Public Health Association
مواضيع طبية MeSH: Artificial Intelligence* , Population Health* , Public Health*, Humans ; Canada ; Professional Role ; Public Health Practice ; Health Equity
مستخلص: Over the past decade, artificial intelligence (AI) has begun to transform Canadian organizations, driven by the promise of improved efficiency, better decision-making, and enhanced client experience. While AI holds great opportunities, there are also near-term impacts on the determinants of health and population health equity that are already emerging. If adoption is unregulated, there is a substantial risk that health inequities could be exacerbated through intended or unintended biases embedded in AI systems. New economic opportunities could be disproportionately leveraged by already privileged workers and owners of AI systems, reinforcing prevailing power dynamics. AI could also detrimentally affect population well-being by replacing human interactions rather than fostering social connectedness. Furthermore, AI-powered health misinformation could undermine effective public health communication. To respond to these challenges, public health must assess and report on the health equity impacts of AI, inform implementation to reduce health inequities, and facilitate intersectoral partnerships to foster development of policies and regulatory frameworks to mitigate risks. This commentary highlights AI's near-term risks for population health to inform a public health response.
(© 2024. The Author(s) under exclusive license to The Canadian Public Health Association.)
References: Angelis, L. D., Baglivo, F., Arzilli, G., Privitera, G. P., Ferragina, P., Tozzi, A. E., & Rizz, C. (2023). ChatGPT and the rise of large language models: The new AI-driven infodemic threat in public health. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1166120.
Artificial Intelligence for Health Task Force. (2020). Building a learning health system for Canadians. Canadian Institute for Advanced Research.
Canadian Public Health Association. (2017). Public health: A conceptual framework. Canadian Public Health Association.
Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. From Reuters: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G.
European Union Agency for Fundamental Rights. (2022). Bias in algorithms: Artificial intelligence and discrimination. Vienna.
Government of Canada. (2022). The Artificial Intelligence and Data Act (AIDA). From Innovation, Science and Economic Development Canada: https://ised-isde.canada.ca/site/innovation-better-canada/en/artificial-intelligence-and-data-act-aida-companion-document.
Greenfield, D., & Bhavnani, S. (2023). Social media: Generative AI could harm mental health. Nature. https://doi.org/10.1038/d41586-023-01693-8. (PMID: 10.1038/d41586-023-01693-837221334)
Guo, L. N., Lee, M. S., Kassamali, B., Mita, C., & Nambudiri, V. E. (2022). Bias in, bias out: Underreporting and underrepresentation of diverse skin types in machine learning research for skin cancer detection-A scoping review. Journal of the American Academy of Dermatology, 157‒159. https://doi.org/10.1016/j.jaad.2021.06.884.
Hold-Lunstad, J. (2022). Social connection as a public health issue: The evidence and systemic framework for prioritizing the “social” in social determinants of health. Annual Reviews of Public Health, 193‒213. https://doi.org/10.1146/annurev-publhealth-052020-110732.
Klein, N. (2023). AI machines aren’t ‘hallucinating’. But their makers are. From The Guardian: https://www.theguardian.com/commentisfree/2023/may/08/ai-machines-hallucinating-naomi-klein.
Norori, N., Hu, Q., Aellen, F. M., Dalia Faraci, F., & Tzovara, A. (2021). Addressing bias in big data and AI: A call for open science. Patterns, 2(10). https://doi.org/10.1016/j.patter.2021.100347.
National Collaborating Centre for Determinants of Health. (2013). Public health roles for improving health equity.
Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and policy considerations for deep learning in NLP. ArXiv. From https://arxiv.org/pdf/1906.02243.pdf.
Suarez-Lledo, V., & Alvarez-Galvez, J. (2021). Prevalence of health misinformation on social media: Systematic review. Journal of Medical Internet Research, 23(1). https://doi.org/10.2196/17187.
World Health Organization. (2023). WHO calls for safe and ethical AI for health. From World Health Organization: https://www.who.int/news/item/16-05-2023-who-calls-for-safe-and-ethical-ai-for-health.
فهرسة مساهمة: Keywords: Artificial intelligence; Determinants of health; Digital technologies; Health equity; Public health
Local Abstract: [Publisher, French] RéSUMé: Au cours de la dernière décennie, l’intelligence artificielle (IA) a commencé à transformer les organismes canadiens en leur promettant une plus grande efficience, de meilleurs processus décisionnels et une expérience client enrichie. Bien qu’elle recèle d’immenses possibilités, l’IA aura des effets à court terme – qui se font d’ailleurs déjà sentir – sur les déterminants de la santé et sur l’équité en santé des populations. Si son adoption n’est pas réglementée, il se peut très bien que les iniquités en santé continuent d’être exacerbées par les préjugés, intentionnels ou non, ancrés dans les systèmes d’IA. Les nouvelles possibilités économiques pourraient être démesurément exploitées par les travailleurs et les travailleuses déjà privilégiés et par les propriétaires des systèmes d’IA, renforçant ainsi la dynamique de pouvoir existante. L’IA pourrait aussi nuire au bien-être des populations en remplaçant les interactions humaines au lieu de favoriser la connexité sociale. De plus, la mésinformation sur la santé alimentée par l’IA pourrait réduire l’efficacité des messages de santé publique. Pour relever ces défis, la santé publique devra évaluer et communiquer les effets de l’IA sur l’équité en santé, en modérer la mise en œuvre pour réduire les iniquités en santé, et faciliter des partenariats intersectoriels pour éclairer l’élaboration de politiques et de cadres réglementaires d’atténuation des risques. Le présent commentaire fait ressortir les risques à court terme de l’IA pour la santé des populations afin d’éclairer la riposte de la santé publique.
تواريخ الأحداث: Date Created: 20240416 Date Completed: 20240529 Latest Revision: 20240613
رمز التحديث: 20240613
مُعرف محوري في PubMed: PMC11151885
DOI: 10.17269/s41997-024-00881-x
PMID: 38625496
قاعدة البيانات: MEDLINE
الوصف
تدمد:1920-7476
DOI:10.17269/s41997-024-00881-x