Shane O'Sullivan1, Nathalie Nevejans2, Colin Allen3, Andrew Blyth4, Simon Leonard5, Ugo Pagallo6, Katharina Holzinger7, Andreas Holzinger8, Mohammed Imran Sajid9, Hutan Ashrafian10. 1. Department of Pathology, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil. 2. Research Center in Law, Ethics and Procedures, Faculty of Law of Douai, University of Artois, France. 3. Department of History and Philosophy of Science, University of Pittsburgh, Pennsylvania. 4. Department of Computing and Mathematics, Faculty of Computing, Engineering and Science, University of South Wales, UK. 5. Department of Computer Science, Johns Hopkins University, Baltimore, Maryland. 6. Department of Jurisprudence, University of Turin, Italy. 7. Secure Business Austria, SBA Research gGmbH, Vienna, Austria. 8. Holzinger Group, HCI-KDD, Institute for Medical Informatics/Statistics. Medical University of Graz, Austria. 9. Department of Upper GI Surgery, Wirral University Teaching Hospital, UK. 10. Department of Surgery and Cancer and Institute of Global Health Innovation Imperial College London, UK.
Abstract
BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). METHODS: We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical technologies (eg, surgical robots), relevant frameworks and standards, cyber security/safety- and legal-systems worldwide. We provide a discussion on unique challenges for robotic surgery faced by proposals made for AI more generally (eg, Explainable AI) and machine learning more specifically (eg, black box), as well as recommendations for developing and improving relevant frameworks or standards. CONCLUSION: We classify responsibility into the following: (1) Accountability; (2) Liability; and (3) Culpability. All three aspects were addressed when discussing responsibility for AI and autonomous surgical robots, be these civil or military patients (however, these aspects may require revision in cases where robots become citizens). The component which produces the least clarity is Culpability, since it is unthinkable in the current state of technology. We envision that in the near future a surgical robot can learn and perform routine operative tasks that can then be supervised by a human surgeon. This represents a surgical parallel to autonomously driven vehicles. Here a human remains in the 'driving seat' as a 'doctor-in-the-loop' thereby safeguarding patients undergoing operations that are supported by surgical machines with autonomous capabilities.
BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). METHODS: We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical technologies (eg, surgical robots), relevant frameworks and standards, cyber security/safety- and legal-systems worldwide. We provide a discussion on unique challenges for robotic surgery faced by proposals made for AI more generally (eg, Explainable AI) and machine learning more specifically (eg, black box), as well as recommendations for developing and improving relevant frameworks or standards. CONCLUSION: We classify responsibility into the following: (1) Accountability; (2) Liability; and (3) Culpability. All three aspects were addressed when discussing responsibility for AI and autonomous surgical robots, be these civil or military patients (however, these aspects may require revision in cases where robots become citizens). The component which produces the least clarity is Culpability, since it is unthinkable in the current state of technology. We envision that in the near future a surgical robot can learn and perform routine operative tasks that can then be supervised by a human surgeon. This represents a surgical parallel to autonomously driven vehicles. Here a human remains in the 'driving seat' as a 'doctor-in-the-loop' thereby safeguarding patients undergoing operations that are supported by surgical machines with autonomous capabilities.
Authors: Iulia Andras; Elio Mazzone; Fijs W B van Leeuwen; Geert De Naeyer; Matthias N van Oosterom; Sergi Beato; Tessa Buckle; Shane O'Sullivan; Pim J van Leeuwen; Alexander Beulens; Nicolae Crisan; Frederiek D'Hondt; Peter Schatteman; Henk van Der Poel; Paolo Dell'Oglio; Alexandre Mottrie Journal: World J Urol Date: 2019-11-27 Impact factor: 4.226
Authors: Lauren R Kennedy-Metz; Pietro Mascagni; Antonio Torralba; Roger D Dias; Pietro Perona; Julie A Shah; Nicolas Padoy; Marco A Zenati Journal: IEEE Trans Med Robot Bionics Date: 2020-11-24