Ethical implications of AI in robotic surgical training: A Delphi consensus statement.

CONTEXT: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them. OBJECTIVES: To provide ethical guidance on developing narrow AI applications for surgical training curricula. We define standardised approaches to developing AI driven applications in surgical training that address current recognised ethical implications of utilising AI on surgical data. We aim to describe an ethical approach based on the current evidence, understanding of AI and available technologies, by seeking consensus from an expert committee. EVIDENCE ACQUISITION: The project was carried out in 3 phases: (1) A steering group was formed to review the literature and summarize current evidence. (2) A larger expert panel convened and discussed the ethical implications of AI application based on the current evidence. A survey was created, with input from panel members. (3) Thirdly, panel-based consensus findings were determined using an online Delphi process to formulate guidance. 30 experts in AI implementation and/or training including clinicians, academics and industry contributed. The Delphi process underwent 3 rounds. Additions to the second and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement. EVIDENCE SYNTHESIS: There was 100% response from all 3 rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of >0.8. There was 100% consensus that there is currently a lack of guidance on the utilisation of AI in the setting of robotic surgical training. Consensus was reached in multiple areas, including: 1. Data protection and privacy; 2. Reproducibility and transparency; 3. Predictive analytics; 4. Inherent biases; 5. Areas of training most likely to benefit from AI. CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts to develop and reach content validation for guidance on ethical implications of AI in surgical training. Providing an ethical foundation for launching narrow AI applications in surgical training. This guidance will require further validation. PATIENT SUMMARY: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.In this paper we provide guidance on ethical implications of AI in surgical training.

Using end-user feedback to optimize the design of the Versius Surgical System, a new robot-assisted device for use in minimal access surgery.

BACKGROUND: Robot-assisted minimal access surgery (MAS) reduces blood loss, recovery time, intraoperative and postoperative complications and pain. However, uptake of robotic MAS remains low, suggesting there are barriers to its use. To overcome these barriers, a new surgical robot system, Versius, was developed based on the needs and feedback of surgeons and surgical teams. METHODS: The surgical robot prototype was designed based on observations in the operating room (OR) and previous interviews with surgeons. Formative studies with surgeons and surgical teams were used to refine the prototype design, resulting in modifications to all components, including the arms, instruments, handgrips and surgeon console. Proof-of-concept cadaver studies were used to further optimize its design by assessing its usability during surgical procedures. RESULTS: Feedback led to the development of a novel, mobile design with independent arm carts and surgical console, linked by supported serial or parallel connections, providing maximum flexibility in the OR. Instrument tips were developed based on surgeons' preferred designs and wristed at the tip providing seven degrees of freedom within the patient. Multiple handgrip designs were assessed by surgeons; of these, a 'game controller' design was rated most popular and usable. An open surgical console design allowing multiple working positions was rated highest by surgeons and the surgical teams. CONCLUSIONS: This surgical robot system has been developed using feedback from end users throughout the design process and aims to minimize barriers to robotic MAS uptake. Additionally, these studies demonstrate system success in the surgical procedures it was designed for. The studies reported here, and further studies of the Versius Surgical System, are intended to align with IDEAL (Idea, Development, Exploration, Assessment, Long-term study) Framework guidance.