Litcius/Paper detail

Limits of trust in medical AI

Joshua Hatherley

2020Journal of Medical Ethics218 citationsDOIOpen Access PDF

Abstract

Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in 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 on 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 on, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely on AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice.

Topics & Concepts

Variety (cybernetics)TrustworthinessClinical PracticeField (mathematics)Computer scienceData scienceMedical practiceArtificial intelligenceDeep learningEngineering ethicsMedicineMedical educationInternet privacyFamily medicinePure mathematicsMathematicsEngineeringArtificial Intelligence in Healthcare and EducationEthics in Clinical ResearchMachine Learning in Healthcare