Limits of trust in medical AI
It addresses concerns about trust deficits in medical practice due to AI reliance, which is an incremental analysis of existing ethical issues.
The paper argues that while AI systems can be reliable for medical tasks like disease detection and prediction, they cannot be trusted, potentially undermining trust in clinical relationships when patients rely on them for decision-making.
Artificial intelligence (AI) is expected to revolutionize the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in a variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI's progress in medicine, however, has led to concerns regarding the potential effects of this technology upon relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI systems can be relied upon, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely upon AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice.