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How Do Different Modes of Verbal Expressiveness of a Student Robot Making Errors Impact Human Teachers’ Intention to Use the Robot?

Published: 09 November 2021 Publication History

Abstract

When humans make a mistake, they often try to employ some strategies to manage the situation and possibly mitigate the negative effects of the mistake. Robots that operate in the real world will also make errors and therefore might benefit from such recovery strategies. In this work, we studied how different verbal expression strategies of a trainee humanoid robot when committing an error after learning a task influence participants’ intention to use it. We performed a virtual experiment in which the expression modes of the robot were as follows: (1) being silent; (2) verbal expression but ignoring any errors; or (3) verbal expression while mentioning any error by apologizing, as well as acknowledging and justifying the error. To simulate teaching, participants remotely demonstrated their preferences to the robot in a series of food preparation tasks; however, at the very end of the teaching session, the robot made an error (in two of the three experimental conditions). Based on data collected from 176 participants, we observed that, compared to the mode where the robot remained silent, both modes where the robot utilized verbal expression could significantly enhance participants’ intention to use the robot in the future if it made an error in the last practice round. When no error occurred at the end of the practice rounds, a silent robot was preferred and increased participants’ intention to use.

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Cited By

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  • (2024)On the Effect of Robot Errors on Human Teaching DynamicsProceedings of the 12th International Conference on Human-Agent Interaction10.1145/3687272.3688320(150-159)Online publication date: 24-Nov-2024
  • (2023)Comparing Psychometric and Behavioral Predictors of Compliance During Human-AI InteractionsPersuasive Technology10.1007/978-3-031-30933-5_12(175-197)Online publication date: 19-Apr-2023
  • (2022)Impact of Adopting Robots as Teachers: A Review Study2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)10.1109/ICETECC56662.2022.10069714(1-9)Online publication date: 7-Dec-2022

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            cover image ACM Conferences
            HAI '21: Proceedings of the 9th International Conference on Human-Agent Interaction
            November 2021
            447 pages
            ISBN:9781450386203
            DOI:10.1145/3472307
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            Published: 09 November 2021

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            Author Tags

            1. Robot errors
            2. error recovery
            3. intention to use
            4. social learning

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            HAI '21: International Conference on Human-Agent Interaction
            November 9 - 11, 2021
            Virtual Event, Japan

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            View all
            • (2024)On the Effect of Robot Errors on Human Teaching DynamicsProceedings of the 12th International Conference on Human-Agent Interaction10.1145/3687272.3688320(150-159)Online publication date: 24-Nov-2024
            • (2023)Comparing Psychometric and Behavioral Predictors of Compliance During Human-AI InteractionsPersuasive Technology10.1007/978-3-031-30933-5_12(175-197)Online publication date: 19-Apr-2023
            • (2022)Impact of Adopting Robots as Teachers: A Review Study2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)10.1109/ICETECC56662.2022.10069714(1-9)Online publication date: 7-Dec-2022

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