Humanizing AI in medical training: ethical framework for responsible design

Abstract

The increasing use of artificial intelligence (AI) in healthcare has brought about numerous ethical considerations that push for reflection. Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical principles and promote equitable healthcare outcomes for both medical practitioners trainees and patients. This perspective article provides an ethical framework for responsibly designing AI systems in medical training, drawing on our own past research in the fields of electrocardiogram interpretation training and e-health wearable devices. The article proposes five pillars of responsible design: transparency, fairness and justice, safety and wellbeing, accountability, and collaboration. The transparency pillar highlights the crucial role of maintaining the explainabilty of AI algorithms, while the fairness and justice pillar emphasizes on addressing biases in healthcare data and designing models that prioritize equitable medical training outcomes. The safety and wellbeing pillar however, emphasizes on the need to prioritize patient safety and wellbeing in AI model design whether it is for training or simulation purposes, and the accountability pillar calls for establishing clear lines of responsibility and liability for AI-derived decisions. Finally, the collaboration pillar emphasizes interdisciplinary collaboration among stakeholders, including physicians, data scientists, patients, and educators. The proposed framework thus provides a practical guide for designing and deploying AI in medicine generally, and in medical training specifically in a responsible and ethical manner.

"Integrating Artificial Intelligence Ethics Education into the Undergraduate Medical Curriculum - a Scoping Review." (Preprint)

“…The importance of AI ethics cannot be undermined, and Topol, E. goes as far as suggesting that an understanding of the ethical challenges related to AI should actually be one of the admission criteria for admission to medical school. Sqalli, M., et al ( 2023) 17 also describe the importance of 'humanising AI in medical training' in order to secure alignment with ethical principles and ensure equity in healthcare. This is also reflected in the Council of Europe's Parliamentary Assembly recommendation 2085 (2020) 18 on AI in healthcare which encourages member states to integrate AI into the curricula of medical education 'with an emphasis on the ethical principles of AI and responsible use of AI applications'.…”

“…At present, the ethics curricula in various medical schools are very diverse and there is no consensus with regard to the best way to teach ethics. Sqalli's proposed ethical framework (Sqalli, M. et al, 2023) 17 is defintely a step in the right direct. Further research is warranted and this should ideally be carried out by medical educators collaborating with bioethicists and other professionals, including data scientists, engineers and possibly sociologists, the aim being to devise a framework that serves as a roadmap to guide curricular design.…”