Communicating Complex Decisions in Robot-Assisted Therapy
This work highlights a key problem for developers and users of robot-assisted therapy, but it is incremental as it builds on existing ideas without presenting new methods or results.
The paper addresses the challenge of enabling Socially Assistive Robots (SARs) to explain complex decisions in therapy, arguing that transparent communication is crucial for trust and effectiveness, and proposes design considerations to guide future research.
Socially Assistive Robots (SARs) have shown promising potential in therapeutic scenarios as decision-making instructors or motivational companions. In human-human therapy, experts often communicate the thought process behind the decisions they make to promote transparency and build trust. As research aims to incorporate more complex decision-making models into these robots to drive better interaction, the ability for the SAR to explain its decisions becomes an increasing challenge. We present the latest examples of complex SAR decision-makers. We argue that, based on the importance of transparent communication in human-human therapy, SARs should incorporate such components into their design. To stimulate discussion around this topic, we present a set of design considerations for researchers.