extended-abstract

The Components of Trust for Collaborating With AI Colleagues

Authors:

Allyson I. Hauptman,

Nathan J. McneeseAuthors Info & Claims

CSCW'22 Companion: Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing

Pages 72 - 75

https://doi.org/10.1145/3500868.3559450

Published: 08 November 2022 Publication History

Abstract

AI technologies are capable of improving the performance and productivity of teams in a variety of work contexts. These advantages may be optimized when the AI agent is considered a full team member. A vital component of the agent’s acceptance as a team member or colleague is the degree to which its human coworkers feel they can trust it. To explore what factors affect the perceptions of an AI agent as a trustworthy team member and a legitimate colleague, we interviewed twenty-two professionals representing various work roles. Our results revealed that the following qualities contribute to professionals’ trust in AI as a colleague: a visual presence reflective of coworkers, engagement in feedback loop and team processes through human communication, and the ability for self-development. These findings contribute to the CSCW community by advancing the current understanding of human-AI teaming and informing the design of trustworthy AI agents into the workplace.

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Cited By

Duan WWeng NScalia MZhang RTuttle JYin XZhou SFreeman GGorman JFunke GTolston MMcNeese N(2024)Getting Along With Autonomous Teammates: Understanding the Socio-Emotional and Teaming Aspects of Trust in Human-Autonomy TeamsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/10711813241272123Online publication date: 21-Oct-2024
https://doi.org/10.1177/10711813241272123
Duan WZhou SScalia MYin XWeng NZhang RFreeman GMcNeese NGorman JTolston M(2024)Understanding the Evolvement of Trust Over Time within Human-AI TeamsProceedings of the ACM on Human-Computer Interaction10.1145/36870608:CSCW2(1-31)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687060
Romero Lauro QBigham JKotturi YFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)Exploring the Role of Social Support When Integrating Generative AI in Small Business WorkflowsCompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681895(485-492)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3678884.3681895
Show More Cited By

Index Terms

The Components of Trust for Collaborating With AI Colleagues
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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Information

Published In

cover image ACM Conferences

CSCW'22 Companion: Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing

November 2022

318 pages

ISBN:9781450391900

DOI:10.1145/3500868

Editors:
Gary Hsieh
University of Washington, Seattle, USA
,
Anthony Tang
University of Toronto, Toronto, Canada
,
Morgan G. Ames
University of California Berkeley, Berkeley, USA
,
Sharon Ding
University of Glasgow, Glasgow, UK
,
Susan Fussell
Cornell University, Ithaca, USA
,
Vera Liao
Microsoft Research, Montreal, Canada
,
Andrés Monroy-Hernández
Princeton University, Princeton, USA
,
Sean Munson
University of Washington, Seattle, USA
,
Irina Shklovski
University of Copenhagen, Copenhagen, Denmark
,
John Tang
Microsoft Research, Sunnyvale, USA

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 November 2022

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Extended-abstract
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CSCW '22

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CSCW '22: Computer Supported Cooperative Work and Social Computing

November 8 - 22, 2022

Virtual Event, Taiwan

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Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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October 18 - 22, 2025

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Cited By

Duan WWeng NScalia MZhang RTuttle JYin XZhou SFreeman GGorman JFunke GTolston MMcNeese N(2024)Getting Along With Autonomous Teammates: Understanding the Socio-Emotional and Teaming Aspects of Trust in Human-Autonomy TeamsProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/10711813241272123Online publication date: 21-Oct-2024
https://doi.org/10.1177/10711813241272123
Duan WZhou SScalia MYin XWeng NZhang RFreeman GMcNeese NGorman JTolston M(2024)Understanding the Evolvement of Trust Over Time within Human-AI TeamsProceedings of the ACM on Human-Computer Interaction10.1145/36870608:CSCW2(1-31)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687060
Romero Lauro QBigham JKotturi YFarzan RLópez CCardoso Llach DQuercia DMustafa MNiu SWong-Villacrés M(2024)Exploring the Role of Social Support When Integrating Generative AI in Small Business WorkflowsCompanion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing10.1145/3678884.3681895(485-492)Online publication date: 11-Nov-2024
https://dl.acm.org/doi/10.1145/3678884.3681895
Kollerup NWester JSkov Mvan Berkel N(2024)How Can I Signal You To Trust Me: Investigating AI Trust Signalling in Clinical Self-AssessmentsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661612(525-540)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661612
Zhan XAbdi NSeymour WSuch J(2024)Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to UseProceedings of the ACM on Human-Computer Interaction10.1145/36373398:CSCW1(1-37)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637339
Tian MEschrich JSterman S(2024)Designing AI with Metaphors: Leveraging Ambiguity and Defamiliarization to Support Design CreativityProceedings of the 16th Conference on Creativity & Cognition10.1145/3635636.3664250(537-541)Online publication date: 23-Jun-2024
https://dl.acm.org/doi/10.1145/3635636.3664250
Zhang MCheng ZShiu SLiang JFang CMa ZFang LWang S(2023)Towards Human-Centred AI-Co-Creation: A Three-Level Framework for Effective Collaboration between Human and AICompanion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3584931.3607008(312-316)Online publication date: 14-Oct-2023
https://dl.acm.org/doi/10.1145/3584931.3607008

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