Let Me Finish First - The Effect of Interruption-Handling Strategy on the Perceived Personality of a Social Agent

This paper presents an experiment with three artificial agents adopting different strategies when being interrupted by human conversational partners. The agent either ignored the interruption (the most common behavior in conversational engines to date), yielded the turn to the human conversational partner right away, or acknowledged the interruption, finished its thought and then responded to the content of the interruption. Our results show that this change in the agent’s conversational behavior had a significant impact on which personality traits people assigned to the agent, as well as how much they enjoyed interacting with it. Moreover, the data also indicates that human interlocutors adapted their own conversational behavior. Our findings suggest that the interactive behavior of an artificial agent should be carefully designed to match its desired personality and the intended conversational dynamics.

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Publication Details

Published
2024-09-16
DOI
https://doi.org/10.1145/3652988.3673916
Citations
1
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.64
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article

Let Me Finish First - The Effect of Interruption-Handling Strategy on the Perceived Personality of a Social Agent

James Kennedy, Reshmashree B. Kantharaju, Maike Paetzel, Ronald Cumbal
1 citations
Personality Traits and Psychology
0.64
article

Let Me Finish First - The Effect of Interruption-Handling Strategy on the Perceived Personality of a Social Agent

James Kennedy, Reshmashree B. Kantharaju, Maike Paetzel, Ronald Cumbal
article en
1 citations

Abstract

This paper presents an experiment with three artificial agents adopting different strategies when being interrupted by human conversational partners. The agent either ignored the interruption (the most common behavior in conversational engines to date), yielded the turn to the human conversational partner right away, or acknowledged the interruption, finished its thought and then responded to the content of the interruption. Our results show that this change in the agent’s conversational behavior had a significant impact on which personality traits people assigned to the agent, as well as how much they enjoyed interacting with it. Moreover, the data also indicates that human interlocutors adapted their own conversational behavior. Our findings suggest that the interactive behavior of an artificial agent should be carefully designed to match its desired personality and the intended conversational dynamics.

Uppsala University (SE), Walt Disney (Switzerland) (CH), Walt Disney (United States) (US)
Reduced inequalities
Openalex Percentile: Top 25%
Personality Traits and Psychology
0.64
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