Proceedings of the AI-HRI Symposium at AAAI-FSS 2020
Shelly Bagchi, Jason R. Wilson, Muneeb I. Ahmad, Christian Dondrup,, Zhao Han, Justin W. Hart, Matteo Leonetti, Katrin Lohan, Ross Mead, Emmanuel, Senft, Jivko Sinapov, Megan L. Zimmerman

TL;DR
This paper discusses the importance of trust in AI and human-robot interaction, emphasizing the need for collaborative research and the role of explainable AI in enhancing trust in HRI applications.
Contribution
It highlights the growing research focus on trust in AI-HRI and advocates for a dedicated forum to advance understanding and collaboration in this area.
Findings
Trust is linked to predictability and reliability in HRI.
Trust is crucial for AI adoption in various societal contexts.
The symposium fosters collaboration on trust and explainable AI in HRI.
Abstract
The Artificial Intelligence (AI) for Human-Robot Interaction (HRI) Symposium has been a successful venue of discussion and collaboration since 2014. In that time, the related topic of trust in robotics has been rapidly growing, with major research efforts at universities and laboratories across the world. Indeed, many of the past participants in AI-HRI have been or are now involved with research into trust in HRI. While trust has no consensus definition, it is regularly associated with predictability, reliability, inciting confidence, and meeting expectations. Furthermore, it is generally believed that trust is crucial for adoption of both AI and robotics, particularly when transitioning technologies from the lab to industrial, social, and consumer applications. However, how does trust apply to the specific situations we encounter in the AI-HRI sphere? Is the notion of trust in AI the…
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Taxonomy
TopicsArtificial Intelligence in Healthcare
