BRIEF RESEARCH REPORT article
Front. Robot. AI
Sec. Human-Robot Interaction
This article is part of the Research TopicThe Impact of Robotic Technologies on Customer Experience and AdoptionView all 5 articles
Transforming Customer Experience in Social Robotics through Explainable and Interpretable Artificial Intelligence Over a Decade
Provisionally accepted
- 1University of the District of Columbia, Washington, D.C., United States
- 2Georgia Institute of Technology, Atlanta, United States
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Over the past decade, the field of social robotics has witnessed significant advancements in enhancing user experience (UX) and customer experience (CX) through the integration of Explainable Artificial Intelligence (XAI) and Interpretable Artificial Intelligence (IAI). This research presents a review that examines the progress made over a decade (2015 – 2025) in developing frameworks for social robotics and human-robot interaction (HRI) that prioritize transparency, trust, and user engagement. The journey began with early efforts to equip social robots with internal needs and motivations, forming the basis for understandable self-explanations. As the field progressed, there was a shift towards more user-centered approaches, autonomous social behavior, and self-explanations. By the early 2020s, researchers had begun to focus on the specific applications of XAI and IAI in social robotics. Past studies have shown that explainable and interpretable AI systems in social robots contributed to sustained user engagement and improved CX over extended periods. Currently, by 2025, the field has matured considerably, with researchers developing comprehensive frameworks that seamlessly integrated UX/CX considerations in social robotics with an emphasis on ethical considerations and societal implications. This research highlights how the past decade has seen remarkable progress in enhancing UX/CX in social robotics through XAI and IAI.
Keywords: customer experience (CX), explainable artificial intelligence (XAI), Human-robot interaction (HRI), Interpretable AI (IAI), Long-Term Human-Robot Trust & Relationships, social robotics, Socio-Behavioral Interpretability, Transparency
Received: 27 Aug 2025; Accepted: 04 Feb 2026.
Copyright: © 2026 Arora, Arora and McIntyre. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Anshu S. Arora
Amit Arora
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