Data over dialogue: Why artificial intelligence is unlikely to humanise medicine
This addresses the ethical and practical implications of AI in healthcare for clinicians and patients, highlighting potential harms rather than benefits.
The paper argues that medical machine learning systems are likely to negatively impact clinician-patient relationships by compromising trust, care, empathy, understanding, and communication, contrary to claims that AI will humanize medicine.
Recently, a growing number of experts in artificial intelligence (AI) and medicine have be-gun to suggest that the use of AI systems, particularly machine learning (ML) systems, is likely to humanise the practice of medicine by substantially improving the quality of clinician-patient relationships. In this thesis, however, I argue that medical ML systems are more likely to negatively impact these relationships than to improve them. In particular, I argue that the use of medical ML systems is likely to comprise the quality of trust, care, empathy, understanding, and communication between clinicians and patients.