Ethische, legale und soziale Implikationen bei der Anwendung künstliche-Intelligenz-gestützter Technologien in der Chirurgie

Wilhelm, Dirk; Hartwig, Regine; McLennan, Stuart; Arnold, Sven; Mildner, Philip; Feußner, H.; Neumuth, Thomas; Bieck, Richard

doi:10.1007/s00104-022-01574-2

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Further concerns include the insufficient protection of data privacy and confidentiality, as well as the lack of informed consent when retrospectively using patient data for training [ 18 , 19 ]. Finally, there is a risk that AI systems will compromise patient autonomy and dignity by making treatment decisions without appropriate oversight [ 15 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

2023

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The increasing use of artificial intelligence (AI) in medicine is associated with new ethical challenges and responsibilities. However, special considerations and concerns should be addressed when integrating AI applications into medical education, where healthcare, AI, and education ethics collide. This commentary explores the biomedical ethical responsibilities of medical institutions in incorporating AI applications into medical education by identifying potential concerns and limitations, with the goal of implementing applicable recommendations. The recommendations presented are intended to assist in developing institutional guidelines for the ethical use of AI for medical educators and students.

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Section: Introductionmentioning

confidence: 99%

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

2023

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“…As it pertains to the study and mitigation of algorithmic bias, previous work is limited in three main ways. First, it has not examined the algorithmic bias of AI systems applied to the data modality of surgical videos 6,40 nor against surgeons 41,42 , thereby overlooking an important stakeholder within medicine. Second, previous work has not studied bias in the real clinical setting characterized by multiple AI systems deployed on the same group of surgeons and across multiple hospitals, with a single exception 43 .…”

Section: Discussionmentioning

confidence: 99%

Human visual explanations mitigate bias in AI-based assessment of surgeon skills

et al. 2023

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Artificial intelligence (AI) systems can now reliably assess surgeon skills through videos of intraoperative surgical activity. With such systems informing future high-stakes decisions such as whether to credential surgeons and grant them the privilege to operate on patients, it is critical that they treat all surgeons fairly. However, it remains an open question whether surgical AI systems exhibit bias against surgeon sub-cohorts, and, if so, whether such bias can be mitigated. Here, we examine and mitigate the bias exhibited by a family of surgical AI systems—SAIS—deployed on videos of robotic surgeries from three geographically-diverse hospitals (USA and EU). We show that SAIS exhibits an underskilling bias, erroneously downgrading surgical performance, and an overskilling bias, erroneously upgrading surgical performance, at different rates across surgeon sub-cohorts. To mitigate such bias, we leverage a strategy —TWIX—which teaches an AI system to provide a visual explanation for its skill assessment that otherwise would have been provided by human experts. We show that whereas baseline strategies inconsistently mitigate algorithmic bias, TWIX can effectively mitigate the underskilling and overskilling bias while simultaneously improving the performance of these AI systems across hospitals. We discovered that these findings carry over to the training environment where we assess medical students’ skills today. Our study is a critical prerequisite to the eventual implementation of AI-augmented global surgeon credentialing programs, ensuring that all surgeons are treated fairly.

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“…Regarding the general ethical debate about smart glasses, ethical issues are related to privacy, safety, justice, change in human agency, accountability, responsibility, social interaction, power and ideology ( 23 ). The specific context of intraoperative support, however, is usually not considered in such generic analyses ( 24 ). Therefore, as sufficient preliminary work has been done, now is the right time to assemble the pieces into a comprehensive picture of ethical issues.…”

Section: Introductionmentioning

confidence: 99%

Intraoperative application of mixed and augmented reality for digital surgery: a systematic review of ethical issues

Ursin,

Timmermann,

Benzinger

et al. 2024

Front. Surg.

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IntroductionHead-mounted displays (HMDs) that superimpose holograms onto patients are of particular surgical interest as they are believed to dramatically change surgical procedures by including safety warning and allowing real-time offsite consultations. Although there are promising benefits of mixed and augmented reality (MR/AR) technologies in surgery, they also raise new ethical concerns. The aim of this systematic review is to determine the full spectrum of ethical issues that is raised for surgeons in the intraoperative application of MR/AR technology.MethodsFive bibliographic databases were searched for publications on the use of MR/AR, HMDs and other devices, their intraoperative application in surgery, and ethical issues. We applied qualitative content analysis to the n = 50 articles included. Firstly, we coded the material with deductive categories derived from ethical frameworks for surgical innovations, complications and research. Secondly, clinical aspects with ethical relevance were inductively coded as ethical issues within the main categories. Thirdly, we pooled the ethical issues into themes and sub-themes. We report our findings according to the reporting guideline RESERVE.ResultsWe found n = 143 ethical issues across ten main themes, namely patient-physician relationship, informed consent, professionalism, research and innovation, legal and regulatory issues, functioning equipment and optimal operating conditions, allocation of resources, minimizing harm, good communication skills and the ability to exercise sound judgement. The five most prevalent ethical issues are “Need for continuous research and innovation”, “Ensuring improvement of the learning curve”, “MR/AR enables new maneuvers for surgeons”, “Ensuring improvement of comfort, ergonomics, and usability of devices,” and “Not withholding MR/AR if it performs better”.ConclusionsRecognizing the evidence-based limitations of the intraoperative MR/AR application is of paramount importance to avoid ethical issues, but clinical trials in surgery pose particular ethical risks for patients. Regarding the digital surgeon, long-term impact on human workforce, potentially harmful “negative training,” i.e., acquiring inappropriate behaviors, and the fear of surveillance need further attention. MR/AR technologies offer not only challenges but significant advantages, promoting a more equitable distribution of surgical expertise and optimizing healthcare. Aligned with the core principle of social justice, these technologies enable surgeons to collaborate globally, improving training conditions and addressing enduring global healthcare inequalities.

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Ethische, legale und soziale Implikationen bei der Anwendung künstliche-Intelligenz-gestützter Technologien in der Chirurgie

Cited by 5 publications

References 7 publications

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

Human visual explanations mitigate bias in AI-based assessment of surgeon skills

Intraoperative application of mixed and augmented reality for digital surgery: a systematic review of ethical issues

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