Robotic-Assisted Surgery - Matters of Activity

Robotic-assisted Surgery (RAS) with its research focus on ›Mastering Digital Cutting‹ is an intersectional project between »Cutting« and »Filtering«. Contemporary RAS are advanced filtering technologies that interface not only surgeons and patients in a novel way (Irani, 2015) but also tie engineers, computer scientists, and designers together. We understand such programmed materiality as »engines of difference« (Irani and Philip, 2018). These »engines of difference« situate in specific sensory and cross-cultural settings and challenge global political, legal, and technological frameworks (Al Asif and Khondoker, 2020; Hachach-Haram, 2021; Kuhn et al., 2021; McNeely, 2020; Mohan et al., 2021; Ponniah et al., 2021). In contemporary RAS surgeons and ›robot‹ co-operate resp. co-laborate (Niewöhner, 2016) in a way where human agency is translated into machine movement since it is a telemanipulation system.

In »Mastering Digital Cutting« we focus on the interaction space of the operating actor mastering his/her tool. In »Filtering«, this is again embedded in the context of the OR, where different systems and actors interact and where the information has to be provided to the different roles in an appropriately interpreted/filtered way. These are two zoom levels that represent the research direction and the overlaps between »Cutting« and »Filtering«.

In »Mastering Digital Cutting« we will follow a prototype-based mode of working. The goal is to create three experimental setups that can be tested and evaluated by practitioners. Each will focus on one specific parameter. The first parameter to be explored is the support needed for the hand to accurately perform the cutting process. The second setup will focus on the connection of hands and the interfaces by using speculative prototyping methods. Here we’re investigating how the user can act with more than two hands in the symbolic space. This part of the program bridges also the research conducted on Robotic Assisted Surgery (RAS) in »Filtering«.

The third part will concentrate on the cooperative tool so to say - a synthesis of the two former parts. Following the question how to design a hybrid interaction space that reflects the human conditions in terms of ergonomics. Because, unlike machines, humans and their brains and muscle systems get tired, which creates an additional burden to perform accurate tasks over time. Through specific prototypes, RAS as a workplace will be tested and iterated.

In RAS, researchers from medicine, informatics, design and cultural history collaborate closely. In this research we aim to explore possible strategies to effectively integrate automated reasoning into human-centered interactive surgical systems. We want to productively employ AI methods while ensuring that people remain in control for a responsible RAS design.

The next generation of RAS systems (e.g., Smart Tissue Autonomous Robot by Johns Hopkins University) are fully automated robots, which always implies an artificial intelligence that takes over former human tasks and decisions. However, we know from other application domains that increased automation imposes several challenges (e. g. Yang et al., 2017). Coupling agency and automation pose vital challenges for responsible design and engineering. This research explores possible strategies to integrate automated reasoning into human-centered interactive surgical systems effectively.

We want to responsibly employ artificial intelligent approaches (e. g., to support clinical decision-making) while ensuring that people remain in control.

In previous research, on the one hand, we investigated ways to provide additional patient information visually to the surgeon using argument reality technologies (e. G. Rüger, Feufel, et al., 2020; Rüger, Moosburner, et al., 2020; Sauer et al., 2017). On the other hand, we have investigated challenges that arise from increased automation, i.e., human-machine collaboration, concerning human decision-making. We proposed and probed, for example, a methodological approach to evaluate human-machine collaboration applications (Mackeprang et al., 2019). Furthermore, we explored levels of interpretability in providing machine learning results (Benjamin and Müller-Birn, 2019) and investigated explanation strategies, i.e., sense-making, of non-technical experts (Benjamin, Kinkeldey, et al., 2022).

We specify different design dimensions of a surgeon-robot partnership. Methodologically, we build on Research through Design (Wiberg, 2014; Zimmerman et al., 2007), where evolutionary prototyping is fundamental (Petruschat, 2012). Within this process, we integrate the participatory design concept of »Speculative Enactments« (Elsden et al., 2017) and develop various configurations of possible human-machine partnerships.

Each configuration represents a viable setup of RAS realized by a Wizard-of-Oz approach. Nonetheless, we carefully prototype both the envisioned partnership and the socio-material configurations. By doing so, we want to understand how the different material configurations affect decision-making processes that are informed by implicit human knowledge. We will conduct workshops in the RAS context to explore how our participants react in each configuration. Based on the insights, we expect a better understanding and concrete design recommendations for a responsible RAS design. We organize our working program in four phases: (1) delineating a theoretical foundation for socio-material practices, (2) specifying a conceptual framework that encompasses the perspectives of surgery, informatics, design, and cultural history, (3) prototyping configurations and their evaluation (based on Situational Analysis), and (4) specifying recommendations for a responsible design and policy implications. We organize these phases within an iterative process that may involve several cycles.