Breaking Bad News in the Era of Artificial Intelligence and Algorithmic Medicine: An Exploration of Disclosure and its Ethical Justification using the Hedonic Calculus

TL;DR

This paper explores the ethical considerations of AI in healthcare, specifically focusing on how the Felicific Calculus can guide morally justified disclosure of bad news in patient interactions.

Contribution

It introduces a novel application of Bentham's Felicific Calculus as an ethical framework for AI-supported medical decision-making and disclosure practices.

Findings

The Felicific Calculus can be adapted to evaluate AI-driven healthcare actions.

Seven domains are identified for assessing moral justification.

The framework offers a quasi-quantitative method for ethical deliberation.

Abstract

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.