Dataset Information

Autonomous surgical robotic systems and the liability dilemma.

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.

SUBMITTER: Jamjoom AAB

PROVIDER: S-EPMC9580336 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Autonomous surgical robotic systems and the liability dilemma.

Jamjoom Aimun A B AAB Jamjoom Ammer M A AMA Thomas Jeffrey P JP Palmisciano Paolo P Kerr Karen K Collins Justin W JW Vayena Effy E Stoyanov Danail D Marcus Hani J HJ

Frontiers in surgery 20220916

<h4>Background</h4>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.<h4>Methods</h4>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 p ...[more]

PMID: 36277285

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Project description:Image-guided and robot-assisted surgeries have found their applications in skullbase surgery. Technological improvements in terms of accuracy also opened new opportunities for robotically-assisted cochlear implantation surgery (RACIS). The HEARO® robotic system is an otological next-generation surgical robot to assist the surgeon. It first provides software-defined spatial boundaries for orientation and reference information to anatomical structures during otological and neurosurgical procedures. Second, it executes a preplanned drill trajectory through the temporal bone. Here, we report how safe the HEARO procedure can provide an autonomous minimally invasive inner ear access and the efficiency of this access to subsequently insert the electrode array during cochlear implantation. In 22 out of 25 included patients, the surgeon was able to complete the HEARO® procedure. The dedicated planning software (OTOPLAN®) allowed the surgeon to reconstruct a three-dimensional representation of all the relevant anatomical structures, designate the target on the cochlea, i.e., the round window, and plan the safest trajectory to reach it. This trajectory accommodated the safety distance to the critical structures while minimizing the insertion angles. A minimal distance of 0.4 and 0.3 mm was planned to facial nerve and chorda tympani, respectively. Intraoperative cone-beam CT supported safe passage for the 22 HEARO® procedures. The intraoperative accuracy analysis reported the following mean errors: 0.182 mm to target, 0.117 mm to facial nerve, and 0.107 mm to chorda tympani. This study demonstrates that microsurgical robotic technology can be used in different anatomical variations, even including a case of inner ear anomalies, with the geometrically correct keyhole to access to the inner ear. Future perspectives in RACIS may focus on improving intraoperative imaging, automated segmentation and trajectory, robotic insertion with controlled speed, and haptic feedback. This study [Experimental Antwerp robotic research otological surgery (EAR2OS) and Antwerp Robotic cochlear implantation (25 refers to 25 cases) (ARCI25)] was registered at clinicalTrials.gov under identifier NCT03746613 and NCT04102215.Clinical trial registrationhttps://www.clinicaltrials.gov, Identifier: NCT04102215.

Dataset Information

Autonomous surgical robotic systems and the liability dilemma.

Background

Methods

Results

Conclusions

Publications

Autonomous surgical robotic systems and the liability dilemma.

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