Breaking Bad News in the Era of Artificial Intelligence and Algorithmic Medicine: An Exploration of Disclosure and its Ethical Justification using the Hedonic Calculus
This addresses ethical decision-making for clinicians and patients in AI-driven medicine, but it is incremental as it adapts an existing philosophical framework to a new context.
The paper tackles the ethical challenge of disclosing bad news like imminent death in AI-supported healthcare by applying Jeremy Bentham's Felicific Calculus to assess moral justification across seven domains, showing how this framework can be used to evaluate AI actions.
An appropriate ethical framework around the use of Artificial Intelligence (AI) in healthcare has become a key desirable with the increasingly widespread deployment of this technology. Advances in AI hold the promise of improving the precision of outcome prediction at the level of the individual. However, the addition of these technologies to patient-clinician interactions, as with any complex human interaction, has potential pitfalls. While physicians have always had to carefully consider the ethical background and implications of their actions, detailed deliberations around fast-moving technological progress may not have kept up. We use a common but key challenge in healthcare interactions, the disclosure of bad news (likely imminent death), to illustrate how the philosophical framework of the 'Felicific Calculus' developed in the 18th century by Jeremy Bentham, may have a timely quasi-quantitative application in the age of AI. We show how this ethical algorithm can be used to assess, across seven mutually exclusive and exhaustive domains, whether an AI-supported action can be morally justified.