Adoption of new technologies in surgery is appropriately slow to allow for the accumulation of evidence to support the use of such technology.
In the automotive industry, cars are defined by 6 levels of automation ranging from no automation to full automation, and automation for surgical robots can similarly be considered on 6 levels.
Important considerations for the implementation of autonomous surgical robots include patient safety, cost, surgical education, and surgical credentialing.
A large-scale effort at sharing quantitative operative data, known as the collective surgical consciousness, will likely be needed to enable research that can lead to generalizable results in artificial intelligence–enabled surgery.
Prior chapters introduced and explored the current state of artificial intelligence (AI) in surgery and opined on specific areas under development in surgical AI. We have seen how various machine learning techniques are having impact on risk prediction and patient selection (Chapters 3 and 9); how natural language processing is alleviating documentation burden and catalyzing clinical workflows (Chapters 5 and 13); and how computer vision has been augmenting intraoperative data streams to allow for more quantitative analysis of surgical events (Chapter 6). Deep learning has had a significant impact across many subfields in AI and has sped the application of AI to surgical environments (Chapters 4, 7, and 11). Robotics, despite significant advances in technology and availability for nearly 2 decades as a surgical tool, is still relatively early in terms of its maturity in many surgical specialties (Chapter 12). The pace of adoption of surgical technology such as robotics and AI has been variable.
Surgery is certainly a conservative profession. Given the stakes at hand (ie, patient lives), adoption of new technologies is appropriately slow to allow for the accumulation of evidence to support the use of such technology. It is therefore not surprising that automation has not entered surgery, where highly complex, unique physiologic and pathophysiologic conditions are treated by humans who, after training for a decade or more, must perform at the peak of their technical skill, critical assessment, and judgment. Surgeons are tasked with demonstrating exceptional coordination between their eyes and hands to deliver the finest and most precise movements, to the point that the phrase “surgical precision” epitomizes the pinnacle of precision in other professions and industries. Furthermore, surgeons have a duty to ensure that any technology is introduced with the goal of improving patient care and preventing patient harm (Chapter 14).
However, as described in Chapter 12, advances in digital technologies have catalyzed conversations and inspired dreams of what an autonomous operation might entail. Furthermore, advances in automated identification of operative steps, instruments, and events through deep learning (Chapters 4, 6, 10, and 11) raise the possibility that clinical decision support from AI could give way ...