Evidence map›Paper›PMID 36277285›Full record

ArticleFrontiers in surgery2022

Autonomous surgical robotic systems and the liability dilemma.

Aimun A B Jamjoom, Ammer M A Jamjoom, Jeffrey P Thomas, Paolo Palmisciano, Karen Kerr, Justin W Collins, Effy Vayena, Danail Stoyanov, Hani J Marcus, iRobotSurgeon Collaboration

Abstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Liability in Telesurgery: Navigating Legal, Ethical, and Cross-Border Challenges in the Era of Global Surgical Care.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. The Emperor's new clothes.Surgery open science · 2024
    Article
  10. Review
  11. Review
  12. Article
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

10 authors.

Aimun A B JamjoomCentre for Clinical Brain Sciences, Edinburgh University, Edinburgh, United Kingdom.
Ammer M A JamjoomDepartment of Trauma and Orthopaedic Surgery, Leeds General Infirmary, Leeds, United Kingdom.
Jeffrey P ThomasDepartment of Management, London School of Economics, London, United Kingdom.
Paolo PalmiscianoDepartment of Neurosurgery, Trauma and Gamma Knife Center, Cannizzaro Hospital, Catania, Italy.
Karen KerrDigital Surgery, Medtronic Ltd, London, United Kingdom.
Justin W CollinsDivision of Surgery and Interventional Science, Research Department of Targeted Intervention, University College London, London, United Kingdom.
Effy VayenaInstitute of Translational Medicine, ETH Zurich, Zurich, Switzerland.
Danail StoyanovDigital Surgery, Medtronic Ltd, London, United Kingdom.
Hani J MarcusWellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, United Kingdom.
iRobotSurgeon Collaboration

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Advances in machine learning and robotics have allowed the development of increasingly autonomous robotic systems which are able to make decisions and learn from experience. This distribution of decision-making away from human supervision poses a legal challenge for determining liability. Methods: The iRobotSurgeon survey aimed to explore public opinion towards the issue of liability with robotic surgical systems. The survey included five hypothetical scenarios where a patient comes to harm and the respondent needs to determine who they believe is most responsible: the surgeon, the robot manufacturer, the hospital, or another party. Results: A total of 2,191 completed surveys were gathered evaluating 10,955 individual scenario responses from 78 countries spanning 6 continents. The survey demonstrated a pattern in which participants were sensitive to shifts from fully surgeon-controlled scenarios to scenarios in which robotic systems played a larger role in decision-making such that surgeons were blamed less. However, there was a limit to this shift with human surgeons still being ascribed blame in scenarios of autonomous robotic systems where humans had no role in decision-making. Importantly, there was no clear consensus among respondents where to allocate blame in the case of harm occurring from a fully autonomous system. Conclusions: The iRobotSurgeon Survey demonstrated a dilemma among respondents on who to blame when harm is caused by a fully autonomous surgical robotic system. Importantly, it also showed that the surgeon is ascribed blame even when they have had no role in decision-making which adds weight to concerns that human operators could act as "moral crumple zones" and bear the brunt of legal responsibility when a complex autonomous system causes harm.

Indexed as

autonomousliabilitypublic opinionroboticssurgery

Identifiers

PMID36277285
PMCPMC9580336

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.