A SYNTHESIS OF THE ETHICAL AND RESPONSIBILITY FRAMEWORK FOR BIOMEDICAL ENGINEERS IN THE ERA OF ARTIFICIAL INTELLIGENCE FOR HEALTHCARE INSTITUTIONS.

Abstract

       Artificial intelligence (AI) and big data analytics are increasingly woven into health service delivery, supporting disease diagnosis, analysis of clinical data, and bedside decision-making in hospitals and clinics in Thailand. As these tools move from pilot projects into routine practice, they bring long-standing ethical questions to the surface, including concerns about transparency, algorithmic fairness, protection of sensitive health information, and the distribution of professional responsibility, particularly for biomedical engineers who design, implement, and maintain medical AI systems. In this article, we draw together research studies, policy papers, and international standards on medical AI, alongside concepts from bioethics, socio-technical systems theory, and the Learning Health System literature, to clarify what responsible use of AI in healthcare should entail for the Thai context. Using a synthetic literature review, we examine how technical design choices, organizational arrangements, and public policy interact to shape both the risks and benefits of AI and the forms of oversight that are realistic in clinical settings. Building on this analysis, we propose a practical framework for healthcare organizations consisting of seven mutually reinforcing elements: ethical foundations, professional responsibility, technical robustness and safety, clinical integration with human oversight, organizational governance, legal and regulatory alignment, and continuous monitoring and learning across the AI model lifecycle. The framework is intended to guide policymakers, hospital leaders, and biomedical engineers in developing, procuring, and supervising medical AI systems in ways that are context-appropriate and ethically defensible in Thailand, in line with emerging international discussions on AI ethics in healthcare.