Ethical Challenges of Robotics in Healthcare

desafíos éticos de la robótica

In recent decades, the relationship between robotics and healthcare has reached unprecedented levels. Technological advances in this field continue to enhance diagnostic accuracy, patient care efficiency, and the optimization of medical treatments. However, this rapid development is not without fundamental ethical controversies that must be addressed from the perspectives of both healthcare professionals and technology developers. From Inrobics, we want to briefly explore the ethical challenges of robotics in healthcare.

In particular, we will focus on five critical aspects. Firstly, we will discuss the privacy and security of data, equity in the development of artificial intelligence (AI), and the responsibility and decision-making of healthcare professionals. Additionally, we will examine autonomy in machines and the need for human supervision, as well as informed patient consent.

Privacy and Security of Data: One of the ethical challenges in the integration of robotics into healthcare is the management of privacy and the security of patients’ medical data.

Robotic systems and AI in healthcare collect and store a vast amount of sensitive patient information, ranging from medical histories to biometric data. This accumulation raises significant concerns regarding privacy and the possibility of information falling into the wrong hands.

To address this challenge, it is essential to implement robust cybersecurity measures and ensure compliance with data privacy regulations, especially those outlined in the European Union’s General Data Protection Regulation (GDPR) and Spain’s Law on Information Society Services and Electronic Commerce (LSSI). Additionally, developers of medical technologies should design systems that allow patients greater control over their data, requiring informed consent for its use.

Equity in AI Development

Another significant ethical challenge in robotics is related to equity in the development and implementation of artificial intelligence in healthcare. While AI has the potential to improve healthcare overall, there is a risk that its benefits may not be distributed equitably. This can occur due to biases in the data used to train algorithms or a lack of access to advanced technologies in certain communities. To address this issue, developers of AI in healthcare must strive to eliminate biases in data and algorithms. They should work collaboratively with healthcare professionals to ensure that solutions are culturally sensitive and accessible to all demographic groups.

Responsibility and Decision-Making

The increasing autonomy of robotic systems and AI raises crucial questions about responsibility and decision-making in the medical field. Who is legally responsible if an algorithm makes an error in diagnosing or treating a patient? How is the line defined between the responsibility of the healthcare professional and the responsibility of the system developer? Can a robotic and AI system be held accountable as an active subject of a crime and be directly responsible for patient harm?

It is essential to establish clarity regarding legal and ethical responsibility in the use of advanced medical technologies. This requires creating specific standards and regulations for robotic healthcare and defining who has the ultimate responsibility in cases of medical decision-making errors.

Autonomy and Human Supervision

The autonomy of machines in healthcare is an ongoing debate. While automation can increase efficiency and reduce human error, maintaining a proper balance between machine autonomy and human supervision is crucial. This is particularly sensitive in the case of robotic surgery, where advancements seem indisputable. To what extent can we trust a robot or algorithm to make medical decisions without human intervention?

In critical situations such as complex surgeries or delicate medical diagnoses, human supervision remains crucial. Decision-making must be shared between specialized medical professionals and automated systems to ensure both patient safety and the quality of care.

Informed Patient Consent

Lastly, informed patient consent becomes more complex with the introduction of robotic and AI technologies in healthcare. Among the ethical challenges posed here is educating patients about their health issues and the appropriateness of a procedure or therapy involving the relevant technology. Patients must understand not only the proposed treatment but also how advanced technologies may impact their well-being and privacy. Additionally, they should have the ability to provide or decline informed consent.

Healthcare professionals not only have the responsibility to clearly explain to patients the use of technology in their care but also to ensure that patients understand the ethical implications and potential risks. This ensures that patients play an active role in their treatment decisions and can make informed choices about the inclusion of robotic technologies in their healthcare. Acceptance under these conditions goes beyond a simple disclaimer of responsibilities.

Recommendations for Addressing Ethical Challenges in Robotic Healthcare

In 2014, the Reflection Commission on the Ethics of Research in Digital Science and Technology of the Allistene alliance (CERNA) proposed relevant recommendations for our topic. These were republished by the European Parliament:

  1. Medical Ethics: Researchers and developers in restorative or assistive robotics must establish coordination with medical professionals and patients. The goal is to consider patient independence and integrity, as well as the protection of their privacy, as part of medical ethics principles and care effectiveness and safety requirements. This should be addressed beyond legal frameworks, allowing for individual adjustments case by case rather than applying a general rule, relying on ethical thinking and deliberation. Researchers should seek and comply with opinions published by operational medical ethics committees. The idea is to establish a connection between emerging robotic technology and positions outlined in such resolutions.
  2. Autonomy and Integrity: Developers creating restorative robotic systems should strive to preserve the autonomy of the individuals using them. Specifically, solutions should keep patients in control of their actions to the extent possible. Furthermore, developers should aim to preserve the integrity of functions distinct from those being rehabilitated.
  3. Reversibility: Those working on robotic devices for human enhancement have the duty to ensure that the resulting adjustments remain reversible. In other words, the removal of devices should not cause harm to the person or cause them to lose initial functions.
  4. Social Effects of Enhancement: Developers must investigate the social effects of human enhancement induced by built devices. This includes effects on the social behavior of enhanced individuals and, reciprocally, on the social behavior of non-enhanced individuals.

Our Social Robotics Rehabilitation Solution Upholds These Ethical Principles

Indeed, Inrobics Rehab, the rehabilitation solution based on social robotics and AI that we developed at Inrobics, has allowed us to understand and apply the explained considerations. Through research and continuous improvements, we have refined this personalized, empathetic, and flexible rehabilitation service. Our goal is not only to increase its effectiveness and accessibility for patients but also to comply with established ethical precepts in healthcare. Of course, we also take into account regulations on personal data protection, such as the GDPR and the LSSI.

Inrobics Rehab features ALMA, our proprietary development software. This consists of a social AI that enhances the performance of the robots and enables their interaction with patients and healthcare professionals. This component allows them to adapt to the needs and various situations in the therapeutic field. ALMA reasons like clinical experts, thanks to machine learning techniques and decision-making systems. In this way, we create an intelligent robot capable of interacting with patients and guiding a rehabilitation session, following the prescription set by the professional. In other words, the system doesn’t make decisions in isolation.

Discover it with a free demo of our solution!

Picture of Fernando Fernández

Fernando Fernández

Full Professor in the Department of Computer Science at Universidad Carlos III de Madrid (UC3M) since October 2005 and former CEO of Adact Solution, SL. He has received various awards and grants, such as the predoctoral FPU fellowship from the Ministry of Education (MEC) and the MEC-Fulbright postdoctoral fellowship. In 2020, he was honored with one of the JPMorgan AI Research Awards. He has published more than 50 articles in journals and conferences in the field of AI. Since July 2022, he is on sabbatical as a Visiting Researcher at Texas Robotics, University of Texas at Austin, conducting his research and laying the groundwork for internationalization. A distinguished professional with solid international training and experience in technology and innovation. He is driven by the desire to apply rigorous scientific methods to develop and validate innovative solutions in the health and technology sectors.