AI knows best? Avoiding the traps of paternalism and other pitfalls of AI-based patient preference prediction.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

6 citing papers in PubMed.

1. AI assisted triage of UK patients in mental health care services: a qualitative focus group study of patients' attitudes.BMC psychiatry · 2026
   Article
2. Artificial autonomy and algorithmic paternalism: AI shaping human autonomy and decision-making.Frontiers in artificial intelligence · 2026
   Article
3. The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.Journal of medical Internet research · 2025
   Article
4. Biases in AI: acknowledging and addressing the inevitable ethical issues.Frontiers in digital health · 2025
   Review
5. A Personalized Patient Preference Predictor for Substituted Judgments in Healthcare: Technically Feasible and Ethically Desirable.The American journal of bioethics : AJOB · 2024
   Article
6. Indecision on the use of artificial intelligence in healthcare-A qualitative study of patient perspectives on trust, responsibility and self-determination using AI-CDSS.Digital health
   Article

Corrections and comments

• Comment on
  Ethics of the algorithmic prediction of goal of care preferences: from theory to practice.2023
• Comment on
  What you believe you want, may not be what the algorithm knows.2023
• Comment on
  For the sake of multifacetedness. Why artificial intelligence patient preference prediction systems shouldn't be for next of kin.2023
• Comment on
  Artificial Intelligence algorithms cannot recommend a best interests decision but could help by improving prognostication.2023
• Comment on
  Fracking our humanity.2023
• Comment on
  Artificial intelligence paternalism.2023

Authors and funding

3 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

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