Predicting and preferring
Bibliographic Data
| ID | 21335334 |
|---|---|
| Authors | Nathaniel Sharadin (0000-0002-4610-664X, University of Hong Kong, corresponding author) |
| Year | 2025 |
| Volume | 68 |
| Issue | 4 |
| Pages | 1121-1132 |
| Publication date | 2025-04-21 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Inquiry (JOURNAL) |
| Journal identifiers | ISSN: 0020-174X • E-ISSN: 1502-3923 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/0020174x.2023.2261493 |
| OpenAlex | W4387058427 |
| Language | EN |
| Citations received | 2 |
| References cited | 41 |
The use of machine learning, or ‘artificial intelligence’ (AI) in medicine is widespread and growing. In this paper, I focus on a specific proposed clinical application of AI: using models to predict incapacitated patients’ treatment preferences. Drawing on results from machine learning, I argue this proposal faces a special moral problem. Machine learning researchers owe us assurance on this front before experimental research can proceed. In my conclusion I connect this concern to broader issues in AI safety
Criticism · Political science · Artificial Intelligence · Computer Science · Ethics in Clinical Research · Ethics in medical practice · Law · Palliative Care and End-of-Life Issues · Psychology
Rethinking Informed Consent in Bioethics
The Accuracy of Surrogate Decision Makers
Strictly Proper Scoring Rules, Prediction, and Estimation
Nudges, Nudging, and Self-Guidance Under the Influence
Autonomy-based criticisms of the patient preference predictor
The Patient preference predictor and the objection from higher-order preferences
Ethics of the algorithmic prediction of goal of care preferences
For the sake of multifacetedness. Why artificial intelligence patient preference prediction systems shouldn’t be for next of kin
Should Aggregate Patient Preference Data Be Used to Make Decisions on Behalf of Unrepresented Patients
The Effectiveness of Interventions to Increase Advance Directive Completion Rates
Flooding the Zone
Nudge
The Effects of Mere Exposure on Liking for Edible Substances
Repeated taste exposure increases liking for vegetables by low-income elementary school children
Reward tampering problems and solutions in reinforcement learning
Salience theory of mere exposure
| Citations per year | 2 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |