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Culture, Errors, and Rapport-building Dialogue in Social Agents

Published: 05 November 2018 Publication History

Abstract

This work explores whether culture impacts the extent to which social dialogue can mitigate (or exacerbate) the loss of trust caused when agents make conversational errors. Our study uses an agent designed to persuade users to agree with its rankings on two tasks. Participants from the U.S. and Japan completed our study. We perform two manipulations: (1) The presence of conversational errors -- the agent exhibited errors in the second task or not; (2) The presence of social dialogue -- between the two tasks, users either engaged in a social dialogue with the agent or completed a control task. Replicating previous research, conversational errors reduce the agent's influence. However, we found that culture matters: there was a marginally significant three-way interaction with culture, presence of social dialogue, and presence of errors. The pattern of results suggests that, for American participants, social dialogue backfired if it is followed by errors, presumably because it extends the period of good performance, creating a stronger contrast effect with the subsequent errors. However, for Japanese participants, social dialogue if anything mitigates the detrimental effect of errors; the negative effect of errors is only seen in the absence of a social dialogue. Agent design should therefore take the culture of the intended users into consideration when considering use of social dialogue to bolster agents against conversational errors.

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    cover image ACM Conferences
    IVA '18: Proceedings of the 18th International Conference on Intelligent Virtual Agents
    November 2018
    381 pages
    ISBN:9781450360135
    DOI:10.1145/3267851
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 05 November 2018

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    Author Tags

    1. Social agents
    2. conversational errors
    3. culture
    4. influence
    5. rapport
    6. social dialogue

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    IVA '18
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    IVA '18: International Conference on Intelligent Virtual Agents
    November 5 - 8, 2018
    NSW, Sydney, Australia

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    IVA '18 Paper Acceptance Rate 17 of 82 submissions, 21%;
    Overall Acceptance Rate 53 of 196 submissions, 27%

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    • (2024)TECHNOLOGICAL SOLUTIONS BASED ON ARTIFICIAL INTELLIGENCE IN TEACHING FOREIGN LANGUAGES: AN ANALYTICAL REVIEWMoscow University Bulletin. Series 19. Linguistics and Intercultural Communication10.55959/MSU-2074-1588-19-27-2-227:№2_2024(18-37)Online publication date: 6-Jul-2024
    • (2024)Enhancing Virtual Human Interactions by Designing a Real-Time Dialog Filter for Mitigating Nonsensical ResponsesProceedings of the 26th Symposium on Virtual and Augmented Reality10.1145/3691573.3691597(51-60)Online publication date: 30-Sep-2024
    • (2024)Exploring the Effects of Self-Correction Behavior of an Intelligent Virtual Character during a Jigsaw Puzzle Co-Solving TaskACM Transactions on Interactive Intelligent Systems10.1145/368800614:3(1-33)Online publication date: 10-Aug-2024
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