Ensuring trust in healthcare robotics: The essential role of explainable AI

Abstract

The combination of robots and artificial intelligence has the potential to transform the current healthcare system. The importance of explainable artificial intelligence (XAI) digs into the fundamental challenges and game-changing solutions driving this critical topic. This chapter focuses on the fundamental issues of building trust in healthcare robotics, with a particular emphasis on XAI. We first explain the challenges associated with AI-integrated healthcare robotics, then look at the outstanding issues that come with integrating robotics into healthcare settings. The discussion revolves around ethical and safety concerns and the complexities of AI systems in healthcare. These challenges set the scenario for XAI’s critical role in tackling these issues. Next, we emphasize the XAI solutions for building trust in healthcare robotics. We explore how XAI enables healthcare robots to operate transparently and reliably. We go deeper into XAI’s crucial role during this transformative journey, demonstrating its capacity to address the key ethical issues related to the use of AI in healthcare. In this section, we look at the accuracy trade-off, explanation depth, contextual understanding, post hoc explainability techniques, evaluation metrics, and the power of XAI. Finally, we illustrate the examples of XAI benefits in healthcare robots, which demonstrate the role of XAI in healthcare robots. Subsequently, we talk about emerging trends and the future of trust-based healthcare robots, mainly focusing on advancing XAI hardware and emerging trends. Finally, we investigate the growing regulatory standards and guidelines, providing insights into the proper use of AI in healthcare. This section provides an overview of the hopeful future of healthcare robots, emphasizing trust as the foundation of its success. In summary, our chapter demonstrates the practical study of healthcare robots and the critical role that XAI plays for potentially changing the future of healthcare delivery. © 2025 Elsevier B.V., All rights reserved.