Cargando…

Autonomous surgical robotic systems and the liability dilemma

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Jamjoom, Aimun A.B., Jamjoom, Ammer M.A., Thomas, Jeffrey P., Palmisciano, Paolo, Kerr, Karen, Collins, Justin W., Vayena, Effy, Stoyanov, Danail, Marcus, Hani J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580336/
https://www.ncbi.nlm.nih.gov/pubmed/36277285
http://dx.doi.org/10.3389/fsurg.2022.1015367
_version_ 1784812365402865664
author Jamjoom, Aimun A.B.
Jamjoom, Ammer M.A.
Thomas, Jeffrey P.
Palmisciano, Paolo
Kerr, Karen
Collins, Justin W.
Vayena, Effy
Stoyanov, Danail
Marcus, Hani J.
author_facet Jamjoom, Aimun A.B.
Jamjoom, Ammer M.A.
Thomas, Jeffrey P.
Palmisciano, Paolo
Kerr, Karen
Collins, Justin W.
Vayena, Effy
Stoyanov, Danail
Marcus, Hani J.
author_sort Jamjoom, Aimun A.B.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9580336
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-95803362022-10-20 Autonomous surgical robotic systems and the liability dilemma Jamjoom, Aimun A.B. Jamjoom, Ammer M.A. Thomas, Jeffrey P. Palmisciano, Paolo Kerr, Karen Collins, Justin W. Vayena, Effy Stoyanov, Danail Marcus, Hani J. Front Surg Surgery 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. Frontiers Media S.A. 2022-09-16 /pmc/articles/PMC9580336/ /pubmed/36277285 http://dx.doi.org/10.3389/fsurg.2022.1015367 Text en © 2022 Jamjoom, Jamjoom, Thomas, Palmisciano, Kerr, Collins, Vayena, Stoyanov, Marcus and Collaboration. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Surgery
Jamjoom, Aimun A.B.
Jamjoom, Ammer M.A.
Thomas, Jeffrey P.
Palmisciano, Paolo
Kerr, Karen
Collins, Justin W.
Vayena, Effy
Stoyanov, Danail
Marcus, Hani J.
Autonomous surgical robotic systems and the liability dilemma
title Autonomous surgical robotic systems and the liability dilemma
title_full Autonomous surgical robotic systems and the liability dilemma
title_fullStr Autonomous surgical robotic systems and the liability dilemma
title_full_unstemmed Autonomous surgical robotic systems and the liability dilemma
title_short Autonomous surgical robotic systems and the liability dilemma
title_sort autonomous surgical robotic systems and the liability dilemma
topic Surgery
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580336/
https://www.ncbi.nlm.nih.gov/pubmed/36277285
http://dx.doi.org/10.3389/fsurg.2022.1015367
work_keys_str_mv AT jamjoomaimunab autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT jamjoomammerma autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT thomasjeffreyp autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT palmiscianopaolo autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT kerrkaren autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT collinsjustinw autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT vayenaeffy autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT stoyanovdanail autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT marcushanij autonomoussurgicalroboticsystemsandtheliabilitydilemma
AT autonomoussurgicalroboticsystemsandtheliabilitydilemma