Evidence map›Paper›PMID 41249441›Full record

ReviewNPJ digital medicine2025

Promoting xenomorphic patient-facing AIs: The case against anthropomorphism in medical AIs.

Stephen R Milford, Emma Herger, Johanna Eichinger, Bernice S Elger

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Stephen R MilfordInstitute for Biomedical Ethics, Basel University, Basel, Switzerland. Stephen.Milford@Unibas.ch.
Emma HergerInstitute for Biomedical Ethics, Basel University, Basel, Switzerland.
Johanna EichingerInstitute for Biomedical Ethics, Basel University, Basel, Switzerland.
Bernice S ElgerInstitute for Biomedical Ethics, Basel University, Basel, Switzerland.

Funding

SNF NRP77 -407740_187263 /1
6 · The paper itself

Abstract

The rapid emergence of patient-facing medical artificial intelligence (MAI) raises pressing questions about its design and impact on healthcare. Current anthropomorphic design strategies, which endow AIs with human-like features, are based on a reductivist understanding of healthcare and risks undermining the integrity of doctor-patient relationships (DPRs) that are foundational to positive health outcomes. This paper argues for a xenomorphic approach-designing MAIs with decidedly non-human, even alien-like characteristics. By distinguishing AIs from human physicians as far as possible, xenomorphic design may avoid direct competition with human relational roles, protecting the ontological distinctiveness of DPRs. Importantly, we suggest that such designs may foster a new class of therapeutic relationships with patients: non-human but nonetheless health-affirming. Analogous to the established benefits of animal-assisted therapies, xenomorphic MAIs could provide complementary sources of trust, comfort, and support without supplanting essential human care. The xenomorphic approach may therefore not only avoid the conceptual and practical challenges of anthropomorphism but also offer an innovative path to expand therapeutic possibilities and improve health outcomes.

Identifiers

PMID41249441
PMCPMC12624071

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.