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Better faulty than sorry: Investigating social recovery strategies to minimize the impact of failure in human-robot interaction
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
2017 (English)In: WCIHAI 2017 Workshop on Conversational Interruptions in Human-Agent Interactions: Proceedings of the first Workshop on Conversational Interruptions in Human-Agent Interactions co-located with 17th International Conference on International Conference on Intelligent Virtual Agents (IVA 2017) Stockholm, Sweden, August 27, 2017., CEUR-WS , 2017, Vol. 1943, p. 19-27Conference paper (Refereed)
Abstract [en]

Failure happens in most social interactions, possibly even more so in interactions between a robot and a human. This paper investigates different failure recovery strategies that robots can employ to minimize the negative effect on people's perception of the robot. A between-subject Wizard-of-Oz experiment with 33 participants was conducted in a scenario where a robot and a human play a collaborative game. The interaction was mainly speech-based and controlled failures were introduced at specific moments. Three types of recovery strategies were investigated, one in each experimental condition: ignore (the robot ignores that a failure has occurred and moves on with the task), apology (the robot apologizes for failing and moves on) and problem-solving (the robot tries to solve the problem with the help of the human). Our results show that the apology-based strategy scored the lowest on measures such as likeability and perceived intelligence, and that the ignore strategy lead to better perceptions of perceived intelligence and animacy than the employed recovery strategies.

Place, publisher, year, edition, pages
CEUR-WS , 2017. Vol. 1943, p. 19-27
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 1943
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-217595Scopus ID: 2-s2.0-85032453885OAI: oai:DiVA.org:kth-217595DiVA, id: diva2:1157130
Conference
1st Workshop on Conversational Interruptions in Human-Agent Interactions, WCIHAI 2017, Stockholm, Sweden, 27 August 2017
Note

QC 20171115

Available from: 2017-11-15 Created: 2017-11-15 Last updated: 2017-11-15Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
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Output format
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