Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment

Sumit Srivastava; Mariët Theune; Alejandro Catala; Chris Reed

doi:10.1145/3631700.3664868

Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment

Sumit Srivastava, Mariët Theune, Alejandro Catala, Chris Reed

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Lexical alignment is a form of personalization frequently found in human-human conversations. Recently, attempts have been made to incorporate it in human-computer conversations. We describe an experiment to investigate the trust of users in the performance of a conversational agent that lexically aligns or misaligns, in a collaborative task. The participants performed a travel planning task with the help of the agent, involving rescuing residents and minimizing the travel path on a fictional map. We found that trust in the conversational agent was not significantly affected by the alignment capability of the agent.

Original language	English
Title of host publication	UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
Publisher	Association for Computing Machinery
Pages	189-194
Number of pages	6
ISBN (Electronic)	9798400704666
DOIs	https://doi.org/10.1145/3631700.3664868
Publication status	Published - 28 Jun 2024
Event	32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024: ACM UMAP 2024 - Cagliari, Italy Duration: 1 Jul 2024 → 4 Jul 2024 Conference number: 32 https://www.um.org/umap2024/

Conference

Conference	32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024
Country/Territory	Italy
City	Cagliari
Period	1/07/24 → 4/07/24
Internet address	https://www.um.org/umap2024/

Keywords

conversational agents
human-agent interaction
lexical alignment
performance trust

ASJC Scopus subject areas

Software

Access to Document

10.1145/3631700.3664868

Cite this

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title = "Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment",

abstract = "Lexical alignment is a form of personalization frequently found in human-human conversations. Recently, attempts have been made to incorporate it in human-computer conversations. We describe an experiment to investigate the trust of users in the performance of a conversational agent that lexically aligns or misaligns, in a collaborative task. The participants performed a travel planning task with the help of the agent, involving rescuing residents and minimizing the travel path on a fictional map. We found that trust in the conversational agent was not significantly affected by the alignment capability of the agent.",

keywords = "conversational agents, human-agent interaction, lexical alignment, performance trust",

author = "Sumit Srivastava and Mari{\"e}t Theune and Alejandro Catala and Chris Reed",

note = "{\textcopyright}2024 Copyright held by the owner/author(s).; 32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024 : ACM UMAP 2024 ; Conference date: 01-07-2024 Through 04-07-2024",

year = "2024",

month = jun,

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doi = "10.1145/3631700.3664868",

language = "English",

pages = "189--194",

booktitle = "UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization",

publisher = "Association for Computing Machinery",

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}

Srivastava, S, Theune, M, Catala, A & Reed, C 2024, Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment. in UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, pp. 189-194, 32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024, Cagliari, Italy, 1/07/24. https://doi.org/10.1145/3631700.3664868

Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment. / Srivastava, Sumit; Theune, Mariët; Catala, Alejandro et al.
UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, 2024. p. 189-194.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment

AU - Srivastava, Sumit

AU - Theune, Mariët

AU - Catala, Alejandro

AU - Reed, Chris

N1 - Conference code: 32

PY - 2024/6/28

Y1 - 2024/6/28

N2 - Lexical alignment is a form of personalization frequently found in human-human conversations. Recently, attempts have been made to incorporate it in human-computer conversations. We describe an experiment to investigate the trust of users in the performance of a conversational agent that lexically aligns or misaligns, in a collaborative task. The participants performed a travel planning task with the help of the agent, involving rescuing residents and minimizing the travel path on a fictional map. We found that trust in the conversational agent was not significantly affected by the alignment capability of the agent.

AB - Lexical alignment is a form of personalization frequently found in human-human conversations. Recently, attempts have been made to incorporate it in human-computer conversations. We describe an experiment to investigate the trust of users in the performance of a conversational agent that lexically aligns or misaligns, in a collaborative task. The participants performed a travel planning task with the help of the agent, involving rescuing residents and minimizing the travel path on a fictional map. We found that trust in the conversational agent was not significantly affected by the alignment capability of the agent.

KW - conversational agents

KW - human-agent interaction

KW - lexical alignment

KW - performance trust

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DO - 10.1145/3631700.3664868

M3 - Conference contribution

AN - SCOPUS:85198971590

SP - 189

EP - 194

BT - UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization

PB - Association for Computing Machinery

T2 - 32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024

Y2 - 1 July 2024 through 4 July 2024

ER -

Trust in a Human-Computer Collaborative Task with or Without Lexical Alignment

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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