Today we have an extra special guest post from ISD Master’s student and CPG partner Melinda Gomez. Please enjoy!
Medical robots are not just the future of health care, but part of the present. Improving health care has become a priority for all medical providers and robots are slowly being implemented as part of the solution. Breakthroughs in research industries continue to spur momentum and investment in the development of artificial intelligence (AI). Their main objective is to achieve a high degree of patient satisfaction (Roa, 2002). But, do they actually improve patient experiences? What are the benefits and risks? Can we really trust artificial intelligence to embody the adaptability of human behavior? These questions spark an ongoing debate among scientists over the effectiveness and implementation of medical robots. Below are some cases that are for and against robotics and AI in patient care as well as a potential solution to bridge the gap.
Medical robots should be used for patient care
Robotics and AI are already a reality and their influence on the world is growing. With advancements in technology, AI has played a key role for education, healthcare, government agencies, and commercial organizations. They are currently being used in a variety of ways. Image- and voice- recognition, data pattern diagnosing, self-driving vehicles, and unmanned aircraft systems are just a few of the many prospects robotics and AI offers. In relation to patient care, robots are being employed as devices in surgical capacities, medical scrub support, pharmacy assistance, and physician-patient interaction. Researchers have discovered that robots not only improve patient motivation but can be social technologies as well.
Benefit 1: Improves motivation and performance
There have been many experiments that support robotic technology to improve learning, motivation and performance. In education, researchers from National Central University have tested how students interact with robots during problem solving exercises. These robots were designed to play real interactive characters within a mixed reality learning environment. As a result, the robots improved the authenticity of problem-solving tasks and also positively affected learning motivation (Chang, Lee, Wang, & Chen, 2010). Increases in performance were discovered as well. Robots may be revolutionizing learning methodologies. AI has the potential to help educators customize instruction for learner-centered experiences. Not only do these robots present more engaging opportunities, but they increase cooperation and motivation in the classroom (Chang, et al., 2010). The goals of using these technologies are to provide learners with scenarios of real-world challenges and present authentic environments to develop necessary knowledge, skills, and abilities.
Benefit 2: Acts as a social technology
Robots are social technologies and can act as an aid to clinical staff members. They now show empathy through facial expressions and gestures that can connect with people on a personal level. Not only that, they embody communication technology by facilitating and moderating interactions with patients and medical staff as well. Robots have the potential to serve as data collectors and gather valuable information about patients emotional and mental states. Also, patients in the hospital can form attachments with robots and there is evidence of positive affects when it comes to interactions. Research has shown that emotional and social bonds with robots for medical procedures were increased after examining measurements of mood, stress, and pain levels (Wang, Pynadath, & Hill, 2015). For more information, watch the video below.
Medical robots are not to be trusted in patient care
At a global scale, hospitals have been slow to fully adopt robotics and artificial intelligence into patient care even though both have been widely used and tested in other industries (Jaiprakash, Roberts, & Crawford, 2016). Some believe that robots are just fancier tools under human control (see Figure 1). However, actually trusting the robot to perform correctly is a huge factor. In a study conducted by Georgia Tech Research Institute, researchers discovered that in emergency situations people trusted robots too much for their own safety. In fact, even after the robot showed consistent unreliability, people still followed the robot’s instructions (Toon, 2016).
Figure 1. MeDi Robot
Risk 1: Ethical and intended use issues
In addition to trust, the design in patient care relies on theories in regards to robotics and AI. There are ethical and social assumptions on behalf of users, but there is very little research to examine if designs of such assumptions are warranted (Lehoux, et. al., 2014). Intended use, complexity, and appropriateness are important factors that should be heavily tested and reinforced prior to implementation in hospitals.In order to use robots to reduce workloads, there should be a greater understanding of where in the process they work.
Risk 2: Privacy, security, regulations, and law
Also, privacy, security, regulation, and law are all components that should be considered. Protecting patients and family privacy is essential. The question to ask is what can be recorded and stored from AI? Video cameras and other devices are built in to promote human interaction. Because of this, there should be constant monitoring for security threats such as potential hacking capabilities for classified medical information.
Proposed Solution: Train robots and humans to interact with each other
To bridge the gap of ethical issues, why not train robots to interact with people and vice versa? With modeling and simulation and instructional design strategies, there is a potential to build an engaging, immersive learning experience to ease the comfort levels of using robots. Also, there is an opportunity to train robots to better represent human behavior and adaptability. The U.S. Navy, for example, created a Human Surrogate Interaction Program as a way to integrate robots in various training procedures (Nassivera, 2015). Through a combination of mixed-reality, robotic collaboration, and on-the-job exercises, Soldiers are to learn how to react and interact with the robots.
On a different note, the biggest challenge for patient care is to make robots compatible with the social environment and rules at the hospital. For people, the challenge may be understanding a robot’s implications to patient care and how to integrate them in the real-world environment. Perhaps physical models of robots or humans can be simulated and used to augment scenario-based training. Instructional content that focuses on teaching practitioners the evolving methods and affordances of robots may be a solution (see Figure 2).
Figure 2. Evolving methods and modes of interaction between humans and robots.
It is only a matter of time when these innovative technologies are fully adopted. As robotics and AI continue to evolve, our training methods should change along with it to meet patient needs and increase satisfaction. Do you feel the solutions above help bridge the gap of human interaction and robots? What do you think should be done to reduce trust issues?
Chang, C., Lee, J., Wang, C., & Chen, G. (2010). Improving the authentic learning experience by integrating robots into the mixed-reality environment. Computers and Education, 55, pp. 1572-1578.
Jaiprakash, A., Roberts, J., & Crawford, R. (2016). Robots in health care could lead to a doctorless hospital. Retrieved from http://theconversation.com/robots-in-health-care-could-lead-to-a-doctorless-hospital-54316
Lehoux, P., Gauthier, P., Williams, B., Miller, F. A., Fishman, J. R., … Vachon, P. (2014). Examining the ethical and social issues of health technology design through the public appraisal of prospective scenarios: a study protocol describing a multimedia-based deliberative method. Implementation Science, 9(1), 81.
Nassivera, J. (2015). U.S. Navy’s new training program to have soldiers work with robots. Retrieved from http://www.hngn.com/articles/64757/20150129/u-s-navys-new-training-program-to-have-soldiers-work-with-robots.htm
Roa, G. N. (2002). How can we improve patient care? Community Eye Health, 15(41), pp. 1-3. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1705904/.
Toon, J. (2016). In emergencies, should you trust a robot? Retrieved from http://www.news.gatech.edu/2016/02/29/emergencies-should-you-trust-robot.
Wang, N., Pynadath, D. V., & Hill, S. (2015). Trust in a human-robot team with automatically generated explanations (Paper Number 15315). Proceedings of the Interservice/industry training, Simulation, and Education Conference (I/ITSEC) Conference, Orlando, FL.