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Cited by 479Social Robot Interaction and HRISpeech and dialogue systemsAI in Service Interactions

Relational agents: a model and implementation of building user trust

Bickmore, Timothy, Cassell, Justine·2001·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
DOI 10.1145/365024.365304
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Abstract

Building trust with users is crucial in a wide range of applications, such as financial transactions, and some minimal degree of trust is required in all applications to even initiate and maintain an interaction with a user. Humans use a variety of relational conversational strategies, including small talk, to establish trusting relationships with each other. We argue that such strategies can also be used by interface agents, and that embodied conversational agents are ideally suited for this task given the myriad cues available to them for signaling trustworthiness. We describe a model of social dialogue, an implementation in an embodied conversation agent, and an experiment in which social dialogue was demonstrated to have an effect on trust, for users with a disposition to be extroverts.

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Crossref · 10.1145/365024.365304

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1 of 1 references verified0 citation errors · 0 not checkable

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  • Bickmore and Cassell (2001) argue that self-disclosure and the chatbot's ability to make the user feel cared for is important for trust.

    “Bickmore and Cassell (2001) also argue that self-disclosure and the chatbot's ability to make the user feel cared for is important for trust.”

    From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as Bickmore and Cassell, 2001

  • Ongoing and long-term interactions present the opportunity for individuals to develop relationships with media agents similar to those with humans.

    “Ongoing and long-term interactions present the opportunity for individuals to develop relationships with media agents similar to those with humans (Bickmore & Cassell, 2001; Bickmore & Picard, 2005).”

    From Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm (2020) · cites this paper as Bickmore & Cassell, 2001

  • Users trust embodied conversational agents more when they engage in small talk.

    “Indeed, past research has shown that users trust embodied conversational agents more when they engage in small talk [5], although this varies by user personality type and level of embodiment of the agent [6].”

    From A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures (2023) · cites this paper as [5]

  • The impact of failures may not perfectly generalize to embodied and text interfaces.

    “As embodied and text interfaces have more potential affordances with which users can judge and interact with the system [5, 6], the impact of failures may not perfectly generalize to these use cases.”

    From A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures (2023) · cites this paper as [5]

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Authors
Bickmore, T., & Cassell, J.
Affiliations
MIT Media Lab (US)
ORCID
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2001-03
Pages
396-403
DOI
10.1145/365024.365304
OpenAlex
W2136058926
Cited by
479
References
1
Citations by year
2026: 30 · 2025: 29 · 2024: 24 · 2023: 21 · 2022: 18 · 2021: 29 · 2020: 34 · 2019: 30 · 2018: 28 · 2017: 16 · 2016: 13 · 2015: 15 · 2014: 15 · 2013: 17 · 2012: 11
FWCI
51.21
Type
conference paper
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
CHI Conference on Human Factors in Computing Systems (publishedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
Keywords
relational agents, trust building, embodied conversational agents, small talk, extraversion, human-agent interaction, conversational strategies

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