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About

Akihiro Maehigashi is a researcher specializing in human-robot interaction (HRI), trust dynamics, and human-AI collaboration. His work centers on understanding how humans form, maintain, and repair trust in robotic and artificial intelligence systems — a critical frontier as intelligent agents become increasingly embedded in everyday life. Maehigashi's most influential contributions explore the fundamental nature of human trust across different agent types. His comparative studies reveal that trust in robots closely resembles trust in AI systems rather than in other humans, while also demonstrating how anthropomorphic physicality shapes these perceptions. Collectively, his papers have accumulated over 30 citations, reflecting growing scholarly interest in this domain. Beyond foundational trust models, Maehigashi investigates the nuanced behavioral and design factors that influence trust dynamics — including robot beep timings, wait times, and apologetic gestures such as bowing for trust repair. His research extends into explainable AI (XAI), examining how attention heatmaps affect human acceptance of AI recommendations. What distinguishes Maehigashi's scholarship is its rigorous experimental methodology, combining online and laboratory studies across diverse cognitive tasks. For students and researchers navigating the complex terrain of human-machine relationships, his body of work offers essential, empirically grounded insights into designing trustworthy robotic and AI systems.