IJBTT

A Blueprint for Responsible AI - Public Health Sector
	© 2024 by IJCTT Journal
	Volume-72 Issue-3
	Year of Publication : 2024
	Authors : Lakshmanan Sethu Sankaranarayanan
	DOI :  10.14445/22312803/IJCTT-V72I3P113

How to Cite?

Lakshmanan Sethu Sankaranarayanan, "A Blueprint for Responsible AI - Public Health Sector," International Journal of Computer Trends and Technology, vol. 72, no. 3, pp. 91-98, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I3P113

Abstract
The integration of Artificial Intelligence (AI) into public health shows significant promise in enhancing disease surveillance, predicting outbreaks, and improving healthcare delivery. However, ethical considerations and potential societal impacts require a comprehensive framework for responsible implementation. This article explores "Responsible AI for the Public Health Sector," emphasizing ethical principles, privacy safeguards, transparency, and equity. Through case studies and ethical frameworks, successful implementations are highlighted, along with challenges in integrating AI into public health practices. The article stresses the moral imperative of ensuring AI in public health serves the greater good, with a focus on accountability, fairness, and community engagement. The aim is to contribute to ongoing discussions on responsible AI, fostering a future where technological innovations align with public health objectives and societal well-being.

Keywords
Artificial Intelligence (AI), Disease Surveillance, Ethical Considerations, Ethical Frameworks, Healthcare Delivery, Outbreak Prediction, Privacy Safeguards and Public Health.

Reference

[1] A. Chhabra et al., “A Conversational AI-Based Intervention for Improved Maternal Health Outcomes in Rural India: A Randomized Controlled Trial,” Journal of Medical Internet Research, vol. 22, no. 11, 2020.
[2] S. Jain et al. “Towards Responsible AI for Maternal Health in Low-Resource Settings: A Case Study from Rural India,” Proceedings of the ACM Conference on Fairness, Accountability, and Transparency, pp. 403-414, 2021.
[3] C.Y. Chew et al., “AI-Powered Early Warning Systems for Infectious Disease Outbreaks: A Systematic Review,” International Journal of Medical Informatics, vol. 144, 2020.
[4] W.L. Yih et al., “Responsible AI for Public Health: Early Warning Systems for Infectious Disease Outbreaks,” Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, pp. 314-320, 2021.
[5] F. Jiang et al., “AI-Powered Personalized Interventions for Chronic Disease Management: A Systematic Review and Meta-Analysis,” Journal of the American Medical Informatics Association, vol. 28, no. 1, pp. 137-148, 2021.
[6] I. Kawachi et al., “Responsible AI for Chronic Disease Management: A Case Study of a Personalized Intervention Platform,” Proceedings of the ACM Conference on Health, Inference, and Learning, pp. 1-10, 2020.