How Ready Are We To Trust Using AI In Medicine? A Study On Compliance To Governance, Engagement Of Stakeholders And Integration Into Medical System

Project Description

Artificial intelligence (AI) is permeating every aspect of 21st century human life. It is now deeply embedded in sectors like logistics, business, engineering and finance. AI is highly pertinent to medicine providing assistance in reading radiology, pathology and endoscopy images, suggesting diagnosis, recommending therapy, surgical decisions and even predicting outcome and survival. While AI’s usefulness and potential impact on medicine is undeniable, real-world deployment is slow relative to other disciplines. A key challenge is the complex issue of “trust” hindering adoption.

Any AI model must be operable within its intended domain to be effective. Its operability is contingent upon first, informed trust, and then, acceptance, by stakeholders. Given the democratisation of AI tools and open availability of data, anyone can develop AI models with unknown biases and unknown utility. Poor development strategy and lack of rigor (both technical and operational), can easily erode trust, or worse, cost human lives. These trust considerations extend beyond technicalities of AI model itself. Social, ethical and legal considerations hold the key to successful deployment and must be examined deeply.

The dimensions of trust and human values were investigated in prior studies. And so, established frameworks and guidelines are now in place. Yet, we are still not seeing widespread adoption and rich data being generated on user experiences in medical setting. This is likely because trustworthiness has not yet been translated into readiness (As analogy, a good product may be on the market, but that does not mean people are willing to try it yet.) Hence, this study will examine three thrusts of adoption readiness via case studies on AI developments across the National Healthcare Group (NHG) medical cluster. We will first identify issues and shortfalls of these 3 thrusts on late phase case studies, develop interventions based on these, and then evaluate for efficacy on early phase case studies. This will in turn, help us “find the wheel in the driver’s seat” as we navigate and negotiate the deployment of next-generation medical practice in the age of AI.

[1] Compliance to standards. How ready are we to comply with AI governance standards? (with emphasis on MOH’s AIHGle)?

[2] Engagement with stakeholders. How ready are people to use AI in healthcare? How do users trust AI in healthcare? Is AI accepted by patients? And is enough being done to facilitate AI-stakeholder interactions?

[3] Integration into ecosystem. How ready is the medical ecosystem for AI embedding?

Health is a high-stakes frontier, and so, examining how ready we are to trust AI prior and during its deployment is critical. Via this project, we will produce insight on real-world deployment issues regarding relevance, applicability and compliance of prevailing governance guidelines. We will produce a framework on auditing compliance, engagement of stakeholders and formulate model of integrating AI protocols into medical eco-system in clinical practice. All these will be crucial in building the trust of stakeholders in the use of AI-tools for future Medicine.

Research Technical Area

  • Humanities and Social Sciences
  • AI Trust and Governance
  • Medicine and Health
  • Artificial & Augmented Intelligence

Benefits to the society

Translate AI into applied medical setting by understanding the critical barriers on trust and accountability across all stakeholders including clinicians, patients, and allied health workers.

Project’s Publications

Team’s Principal Investigator

Joseph SUNG
Lee Kong Chian School of Medicine
Nanyang Technological University

Professor Joseph Sung received his medical degree from The University of Hong Kong (1983), and was conferred PhD in biomedical sciences by the University of Calgary and MD by The Chinese University of Hong Kong (CUHK) subsequently. He holds fellowships from the Royal Colleges of Physicians of Edinburgh, Glasgow, London, and Australia, the American College of Gastroenterology, the American Gastroenterological Association, the Hong Kong College of Physicians, the Hong Kong Academy of Medicine. He is concurrently Mok Hing Yiu Professor of Medicine of CUHK, an Academician of the Chinese Academy of Engineering of PRC, an Academician of the Eurasian Academy of Sciences and Founding Member of the Academy of Sciences of Hong Kong (ASHK).

Recent Notable Awards:
His contributions to the advancement of medical sciences and academic development have been recognised locally and regionally. Here are some notable awards:

  • World Outstanding Chinese Award (the World Chinese Business Investment Foundation and the United World Chinese Association, 2013)
  • Hong Kong Fulbright Distinguished Scholar Award (HKSAR Government, 2014)
  • Class 2, State International Natural Science Award (The Chinese Academy of Sciences, PRC, 2016)

The Team

Co Principal Investigators

TAN Cher Heng, Tan Tock Seng Hospital 
Research Focus: Radiology

XU Hong, Nanyang Technological University (School of Social Sciences)
Research Focus: Neural mechanisms underlying visual perception

LEE Kwan Min, Nanyang Technological University (Wee Kim Wee School of Communication & Information)
Research  Focus: UX (User Experience) research and design, social and psychological effects of ICT (Information and Communication Technologies), and human machine interaction including human computer interaction (HCI), human robot interaction (HRI), and human automobile interaction (HAI)

Bernett LEE, Nanyang Technological University (LKC Medicine)
Research Focus: Biomedical informatics (Graph visualization and workflow development)

Wilson GOH, Nanyang Technological University (LKC Medicine)
Research Focus: Network Theory, Systems Modelling and Biostatistics


KUO Chuo Yew, Tan Tock Seng Hospital
Research Focus: General Gastroenterology and Clinical Hepatology; Clinical Research