Abstract

Surgical AI is no longer a promise on the horizon. Platforms combining robotic assistance, mixed reality navigation, and real-time de- cision support are entering operating rooms. Yet the values embedded in these systems, the choices about whose data they train on, whose bodies they optimise for, and whose autonomy they quietly override, are rarely considered before deployment or revisited as these systems evolve. We present VIRTUES (Values and Impact for Responsible Technological Use in Environments of Surgery), a framework for anticipatory fairness eval- uation in surgical AI. VIRTUES was developed through a focus group, thematic analysis, and design fictions following a fictional surgical AI platform across three temporal horizons, then evaluated by ten indepen- dent raters using structured valence coding. Across these horizons, we find that the most consequential design decisions are neither clearly ben- eficial nor harmful, but Mixed, simultaneously advancing some values while eroding others. Left unresolved, these tensions accumulate until they become the structural conditions of care. By surfacing these ten- sions before they become embedded in practice, VIRTUES supports an- ticipatory fairness evaluation throughout the surgical AI lifecycle.

Links to Paper and Supplementary Materials

Main Paper (Open Access Version): https://papers.miccai.org/miccai-2026-sat/paper/FAIMI-BRIDGE-EPIMI_029.pdf

SharedIt Link: Not yet available

SpringerLink (DOI): Not yet available

Supplementary Material: Not Submitted

Link to Open Review

Open Review Page: https://openreview.net/forum?id=zuqpHsVrCF&nesting=2&sort=date-desc

BibTex

@InProceedings{ElNad_Futures_MICCAISAT2026,
        author = { El-Mufti, Nadine AND Drouin, Simon AND Jannin, Pierre AND Kersten-Oertel, Marta},
        title = { { Futures Before Failures: Design Fictions for Anticipatory Fairness in Surgical AI } },
        booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026 Workshops and Challenges},
        year = {2026},
        publisher = {Springer Nature Switzerland},
        volume = {LNCS 17279},
        month = {pending},
        page = {pending}
}


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