Exploring the Boundaries of Trust in Medical Artificial Intelligence

Abstract

Background: Artificial intelligence (AI) is rapidly transforming the landscape of healthcare, offering promising solutions to various clinical challenges. However, the integration of AI in medical practice raises critical questions about trust in human-AI interactions, particularly in clinical decision-making processes. This study aims to delve into the nuanced dynamics of trust within the realm of medical AI, focusing on the limits and implications of trust in AI systems as they become integral to patient care and clinical decision-making.
Methodology: Through a focal group discussion approach, this research engages healthcare professionals, ethicists, and technologists to explore the complexities surrounding trust in medical AI. Participants will share insights, experiences, and perspectives on the challenges and opportunities presented by AI in healthcare settings.
Results: The discussions are anticipated to shed light on the distinction between reliance and trust in AI, the factors influencing trust in AI systems, and the potential impact of AI on patient-provider relationships. Insights from the focal group discussions will provide a comprehensive understanding of the boundaries of trust in medical AI.
Conclusion: By critically examining the limits of trust in medical AI, this study aims to contribute to the ongoing dialogue on the ethical and practical implications of integrating AI into healthcare. The findings will inform strategies to navigate the evolving landscape of AI in medicine while preserving the essential elements of trust in clinical practice.