A Critical Analysis of Privacy Issues with Healthcare Robots within the Framework of Medical Care Ecology
Academic Writing
By Juhi Khare
8 min read
As healthcare evolves, AI and robotics are reshaping patient care, raising questions about efficiency, ethics, and privacy. Balancing human intuition with automation is key to ensuring technology enhances—rather than replaces—the doctor-patient relationship.
Ecology of Medical Care
‘Ecology’ is a frequently used term that mainly refers to the link between organisms and their surroundings. What we comprehend by ecology in medical assistance also stems from this general notion of ‘ecology’. The term "ecology" in the context of the healthcare system refers to the entire community, including the patient, the treating physician, and all other artifacts. Medical care requires a close-knit community that is united in its commitment to giving the patient the best treatment possible, just like any other customer facing industry.
Stakeholders Involved in Healthcare Ecology
When we talk about medical care ecology, we can observe four major stakeholders that have significant interest in this subject's outcome. The principal stakeholder like any other consumer oriented sector, is the customer or patient. The ultimate goal of the doctors and the other stakeholders united is to deliver the best services to their consumer who is the patient in case of a healthcare system. Next follows the category of ‘providers’ who are the doctors. These are the individuals who deal directly with clients or patients. The insurance agency and government organizations also form up a separate group of stakeholders. Both these groups may not be directly involved in the care delivering activity but play a big part in making the process easy for individuals in need.
Evolution of Medical Care Ecology
When we consider the traditional caring approaches, all we get in the picture is a doctor and a patient. In ancient days these were the only two persons that completed the healthcare ecosystem. With the passage of time, various groups of stakeholders have secured positions within the system, each with their own particular interests and objectives. But the prime goal to satisfy the users demands remains the same over time. In more recent times, we witness a new addition to this environment. Yes, I am talking about medical machines, specifically robots assisting in healthcare services. With the passage of time, the requirements of individuals have evolved and so did the way to deal with those requirements. It is no surprise that we will continue to notice the expansion in the use of artifacts in the field of medicine. The doctors these days not only focus on the physical health of their patients but also equally focus on their emotional and mental wellbeing. Medical machines not only help in lessening the physical stress on human care workers but also assist and replace people from undertaking repeated boring activities at health centers. We can readily observe that the contemporary health business has grown a lot more technology oriented than ever before, and this is projected to rise dramatically in the near future.
Robotization of Healthcare Industry
The medical industry is being increasingly automated, just like every other industry. Robotic nurses and their participation in healthcare-related tasks are heavily marketed. This can be an effect of a study that anticipates the number of senior individuals to be more than the young ones in the future. Therefore, we can foresee an alarming need for the development and deployment of effective healthcare robots. Robots and other machines that can perform the same task repeatedly were invented long ago. The development of helpful robots, however, required some time. One significant component in this is the expectation that machines and robots will adapt to the shifting dynamics of our workplaces. Every patient has a unique set of needs, so before suggesting any treatment, the robots need the information to look up the patient's medical history. This is an extremely sensitive industry where there is no scope of error. The robots must therefore be perfectly trained because otherwise, the results could be deadly. Living in the 21st century, we cannot disregard the upsides of deploying robots for such tasks. But this comes with it’s own set of concerns that need to be taken care of.
Healthcare Robots as Social Actors
Beyer and Holtzblatt [1] emphasize the importance of context and how it greatly affects users' perceptions of and responses to a specific technology in their article on contextual inquiry. This approach applies to robots employed in medical treatment as well because they are the artifacts that interact with the users directly in their homes or hospitals. In some circumstances, healthcare robots might be considered as a subset of social robots. When someone needs medical attention, the situation is already tight and there is no space for errors. In such a scenario if we take an example of a robot that conducts his tasks as a nurse but also chats to the patient and his friends with an intent to facilitate them release stress and keep hopeful of quick recovery of the patient. A relatively new addition to the categories of healthcare robots are the Rehabilitation robots. These robots help the patients recover from their ailments by delivering workouts, etc that accelerates their recuperation. An example of such a robot is The Lokomat (Hocoma, Switzerland) [2], which is an exoskeletal robot to manipulate a patient's hip and knee.
Fig. The Lokomat (Hocoma, Switzerland)
The Lokomat may not be as clever as other healthcare robots like ‘TUG’ Robot from Aethon [3], that keep track of all your data or follow the patient's mobility or even monitor the patient at all times. Although ‘TUG’ is a service robot, it has access to the patient’s daily routine, allergies, medical history and current medical status. All this data is required by him to deliver the best of his service. But a flip side to this can be seen as a threat to the user’s data as his data can be shared without his consent and knowledge. Though these artifacts were intended for the benefit of the patients, they constitute a huge threat on the privacy of the users, be it their data or other tracked information. Robots that are equipped with Artificial Intelligence and cameras are quite likely to disrupt your privacy.
Fig. TUG Robot by Aethon
Privacy Concerns in Healthcare Robots
We can infer from the previous explanation that a user's reaction to such a robot will largely rely on the situation. Usually healthcare robots are utilized in tense situations when the users are more likely to agree on anything the robot asks for as a prerequisite to function effectively without reading the terms and conditions. This somewhat becomes an example of dark UX. “Privacy” in the healthcare arena can be separated into three basic aspects that are: physical privacy, informational privacy and decisional privacy. Research has proven that such robots violate the users physical, psychological and social privacy due to their autonomy and capacity for social bonding [4]. Data privacy of the patients is very important since it helps develop confidence between the patient and the healthcare practitioner. Additionally, it aids in protecting the data from malicious users who can enter from anywhere.
Companies frequently exploit this circumstance to gain access to a wealth of data. This often comprises the patient's medical background and tracking information. In a residential setting, a smart robot not only captures and communicates patient data to the corporation, but it also sends information that it overhears when family members are conversing. All of this information is examined and used to influence users' choices in ways that are advantageous to the business. Many tech behemoths are interested in the healthcare sector for a variety of reasons, including the potential money that proper data synthesis may help the organization generate.
Take Amazon as an example. They have long had an interest in the health sector, and most lately, Amazon has broadened its horizons and made investments in healthcare firms. Why? The data it can gather through these companies' products and turn into significant future income is the reason for all this. An illustrative scenario makes this clear. Imagine a woman is pregnant and she uses the health company’s robot companion to remind her of her daily vitamins and medicines. Now when amazon obtains this data, it will start proposing pregnancy related artifacts like pregnancy pillows and maternity outfits to the woman. The amount of money made by applying the same cycle to thousands of consumers will be enormous. Although the user's privacy was compromised, the corporation nevertheless made a sizable profit. This is why this can be called a dark pattern.
Possible Framework for Ethical Design of Healthcare Robots
Ethics in Human-Computer Interaction (HCI) includes a wide range of subjects including: human welfare, ownership and property, privacy, freedom from bias, universal usability, trust, autonomy, informed consent, and accountability, among others. When we examine this specific circumstance from the user's point of view, we can see the injustice that is occurring to them without their knowledge. In this situation, dark UX might be advantageous for a company's bottom line, but there are always ways to go around it and
make the process visible for the customers because it is their right to fully control their privacy. There are circumstances where a dark pattern may come to the user’s favor but this is not the case here. Therefore, as designers it is our responsibility to take a stand for our users and work towards increasing transparency in such a sensitive domain.
Healthcare robots as huge as TUG and as small as drones might offer the same kind of hazard to the patient’s private data. In this advanced era of technology, it has become so easy to acquire and distribute data that people have started exploiting it. Many frameworks like the ethical framework for the design of drones in public health [5] have been developed by scientists and researchers that can be used while building robots to prevent privacy issues like the ones outlined above. Even better, a designer might use them as examples to develop their own framework for upholding their beliefs.
Fig. Ethical framework for the design of drones in public health [5]
Conclusion
To recapitulate, with reference to the venn diagram, we can understand how the author has envisioned healthcare robots as an artifact that may be seen as a social actor inside the healthcare ecology. The problems with privacy have been covered in considerable detail, and potential frameworks for solving them have been put forth.
Fig. Venn Diagram
Although there are certain general guidelines for ethical design that can serve as an inspiration, they won't always be sufficient on their own. Every artifact needs to be approached with a certain set of ethical considerations. This may vary depending on a variety of factors, including the user's age, skills, and environment. Prospective designers might use straightforward frameworks like the one discussed above as a springboard to begin thinking in this direction and gradually develop their own design ethics. Additionally, as a designer, we are required to design for better experiences without compromising with the company’s aims. Finding the ideal balance between moral design and practical design that also meets the company's expectations for the product will be challenging.
References
[1.] Beyer, H., & Holtzblatt, K. (1998). Contextual inquiry. Defining customer-centered systems, 31.
2.] Krebs, Hermano & Volpe, Bruce. (2015). Robotics: A Rehabilitation Modality. Current Physical Medicine and Rehabilitation Reports. 3. 243-247. 10.1007/s40141-015-0101-6.
3. https://www.intelrealsense.com/autonomous-mobile-roboticsaethon
4. Lutz, C., Schöttler, M., & Hoffmann, C. P. (2019). The privacy implications of social robots: Scoping review and expert interviews. Mobile Media & Communication, 7(3), 412–434. https://doi.org/10.1177/2050157919843961
5. Cawthorne, D. (2022). Robot Ethics: Ethical Design Considerations. In: Herath, D., St-Onge, D. (eds) Foundations of Robotics. Springer, Singapore. https://doi.org/10.1007/978-981-19-1983-1_16