Algorithms advise, humans decide: the evidential role of the patient preference predictor.

J Med Ethics

School of Philosophy, Religion, and History of Science, University of Leeds, Leeds, UK

Published: October 2024

AI Article Synopsis

  • An AI-based 'patient preference predictor' (PPP) aims to assist in healthcare decisions for individuals who cannot make decisions for themselves, using sociodemographic data to estimate patient preferences.
  • The paper discusses a crucial distinction between algorithmic prediction and decision-making, arguing that recent philosophical debates often overlook this difference.
  • The author concludes that while objections to the PPP question its use as the only basis for decisions, they actually support its role as a valuable tool to inform human decision-making in healthcare.

Article Abstract

An AI-based 'patient preference predictor' (PPP) is a proposed method for guiding healthcare decisions for patients who lack decision-making capacity. The proposal is to use correlations between sociodemographic data and known healthcare preferences to construct a model that predicts the unknown preferences of a particular patient. In this paper, I highlight a distinction that has been largely overlooked so far in debates about the PPP-that between algorithmic prediction and decision-making-and argue that much of the recent philosophical disagreement stems from this oversight. I show how three prominent objections to the PPP only challenge its use as the sole determinant of a choice, and actually support its use as a source of evidence about patient preferences to inform human decision-making. The upshot is that we should adopt the evidential conception of the PPP and shift our evaluation of this technology towards the ethics of algorithmic prediction, rather than decision-making.

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Source
http://dx.doi.org/10.1136/jme-2024-110175DOI Listing

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