Mental Models of a Mobile Shoe Rack

Author:

Rueben Matthew1,Klow Jeffrey2,Duer Madelyn2,Zimmerman Eric2,Piacentini Jennifer2,Browning Madison2,Bernieri Frank J.2,Grimm Cindy M.2,Smart William D.2

Affiliation:

1. University of Southern California, CA, USA

2. Oregon State University, Corvallis, OR, USA

Abstract

Most people do not have direct access to knowledge about the inner workings of robots. Instead, they must develop mental models of the robot, a process that is not well understood. This article presents findings from a long-term, in-the-wild, qualitative, hypothesis-generating study of the mental model formation process. The focus was on how (qualitatively) users form mental models of the robot—specifically its perceptual capabilities, rules of behavior, and communication with other humans. Participants of diverse ages had multiple interactions with the robot over six weeks in a non-laboratory setting. The robot’s rules of behavior were changed every two weeks. A novel, non-anthropomorphic robot was created for the study with a realistic use case: storing people’s shoes during a yoga class. This article reports findings from a case study analysis of 28 interviews conducted over six weeks with six participants. These findings are organized into six topics: (1) variability in the rate at which mental models are updated to be more predictive, (2) types of reasoning and hypothesizing about the robot, (3) borrowing from existing mental models and use of imagination, (4) attributing sensing capabilities where there are no visible sensors, (5) judgments about whether the robot is autonomous or teleoperated, and (6) experimenting with the robot. Specific suggestions for future research are given throughout, culminating in a set of study design recommendations. This work demonstrates the fruitfulness of long-term, in-the-wild studies of human-robot interaction, of which mental model formation is a foundational aspect.

Funder

“Socially Aware, Expressive, and Personalized Mobile Remote Presence: Co-Robots as Gateways to Access to K-12 In-School Education,”

NSF NRI

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Teaming with a Robot in Mixed Reality: Dynamics of Trust, Self-Efficacy, and Mental Models Affected by Information Richness;International Journal of Human–Computer Interaction;2024-04-09

2. A Taxonomy of Robot Autonomy for Human-Robot Interaction;Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction;2024-03-11

3. Using Exploratory Search to Learn Representations for Human Preferences;Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction;2024-03-11

4. Meta-cognition about social robots could be difficult, making self-reports about some cognitive processes less useful;Behavioral and Brain Sciences;2023

5. Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings;ACM Transactions on Human-Robot Interaction;2022-09-08

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