Perceptions of Agent Loyalty with Ancillary Users - Robotics Institute Carnegie Mellon University

Perceptions of Agent Loyalty with Ancillary Users

Samantha Reig, Elizabeth Jeanne Carter, Xiang Zhi Tan, Aaron Steinfeld, and Jodi Forlizzi
Journal Article, International Journal of Social Robotics, February, 2021

Abstract

Intelligent agents are part of the smartphones, smart speakers, and home robots that millions of us own and interact with regularly. However, little is known about if or how these agents should be embodied. Additionally, as conversations with agents move from heavily structured and transactional to more flexible and, at times, social, embodiment may play a more nuanced and variable role. This paper describes an experimental study that examined the effects of embodiment and quality of information on people’s perceptions of an intelligent agent. We conducted a 3×2 between-subjects experiment in which participants completed an escape room-like task with the “help” of an artificial personal assistant that had a robotic embodiment, a virtual embodiment, or no embodiment. Participants were given either helpful or unhelpful information about the task. Findings suggest that people can attribute the quality of loyalty to an agent that belongs to someone else and may work on their behalf, and that in the context of a complex problem-solving situation that involves time pressure, people may prefer an embodied robot or a disembodied voice over a virtually embodied agent.

Notes
This study was funded and supported by the National Science Foundation (SES 1734456) and the National Aeronautics and Space Administration (80NSSC19K1133). Thank you to Benjamin Stone and Thomas Von Davier for assistance with coding the video data, and to our colleagues for help with piloting and insightful feedback.

BibTeX

@article{Reig-2021-126781,
author = {Samantha Reig and Elizabeth Jeanne Carter and Xiang Zhi Tan and Aaron Steinfeld and Jodi Forlizzi},
title = {Perceptions of Agent Loyalty with Ancillary Users},
journal = {International Journal of Social Robotics},
year = {2021},
month = {February},
}