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Cited by 553Social Robot Interaction and HRITechnology Adoption and User BehaviourInnovative Human-Technology Interaction

Technology, Humanness, and Trust: Rethinking Trust in Technology

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Marshall University, Lankton, Nancy, McKnight, D. Harrison, Michigan State University, Tripp, John, Baylor University·2015·Journal of the Association for Information Systems
DOI 10.17705/1jais.00411
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Abstract

Information systems (IS) research has demonstrated that humans can and do trust technology. The current trust in technology literature employs two different types of trust in technology constructs. Some researchers use human-like trust constructs (e.g., benevolence, integrity, and ability), while other researchers use system-like trust constructs (e.g., helpfulness, reliability, and functionality). Interestingly, past research shows that both sets of measures influence important dependent variables, but the literature does not explain when one type should be used instead of the other type. In this paper, we use trust, social presence, and affordance theories to shed light on this research problem. We report on two studies. In study 1, we argue first that technologies vary in their perceived “humanness”. Second, we argue that, because users perceive two technologies to differ in humanness, they will develop trust in each technology differently (i.e., along more human-like criteria or more system-like criteria). We study two technologies that vary in humanness to explore these differences theoretically and empirically. We demonstrate that, when the trust construct used aligns well with how human the technology is, it produces stronger effects on selected outcome variables than does a misaligned trust construct. In study 2, we assess whether these technologies differ in humanness based on social presence, social affordances, and affordances for sociality. We find that these factors do distinguish whether technology is more human-like or system-like. We provide implications for trust-in-technology research.

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  • People can hold trust and distrust at the same time, influenced by different sets of factors and considerations.

    “In other words, people can hold trust and distrust at the same time, influenced by different sets of factors and considerations.”

    From Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education (2025) · cites this paper as [69]

    In its discussion of trust’s dimensionality (page unavailable), the paper reports a view that treats trust and distrust as separate constructs. That lends some support to the distinction, but it does not say people hold both at the same time or that different factors influence each. The authors explicitly state that studying distrust is beyond their scope. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • The role of distrust in the adoption of GenAI remains underexplored and insufficiently acknowledged.

    “Although much of the existing research prioritizes trust, and some recent studies have started to explore distrust [69, 125], the role of distrust in the adoption of GenAI remains underexplored and insufficiently acknowledged.”

    From Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education (2025) · cites this paper as [69]

    In the section headed “Lankton et al. / Rethinking Trust in Technology,” the paper says that studying distrust is beyond its scope. This illustrates a trust-focused study that leaves distrust unexamined, but it does not establish that distrust in GenAI adoption is broadly underexplored. Nor does it support the citation-adjacent suggestion that this study explored distrust. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Trust is a complex concept and is built upon human users' interaction and consequent assessment of the system from cognitive, emotional, and social dimensions.

    “Nevertheless, trust is a complex concept and is built upon human users’ interaction and consequent assessment of the system from cognitive, emotional, and social dimensions [91-93].”

    From Generative AI in medical practice: in-depth exploration of privacy and security challenges (2024) · cites this paper as [92]

    The Introduction and Section 2.2 describe users assessing technology through human-like and system-like trusting beliefs; the discussion of social presence also connects social cues and emotion-based qualities to trust. The paper does not present cognitive, emotional, and social dimensions as a three-part account of how trust is built, as the citing sentence implies. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Some scholars have argued that trust and distrust can be two independent constructs in certain contexts.

    “While previous research often views trust and distrust as two extremes of a single dimension or uses these two terms interchangeably-implying high trust means low distrust-some scholars have argued that trust and distrust can be two independent constructs in certain contexts [69, 125].”

    From Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education (2025) · cites this paper as [69]

  • Most IS research nowadays employs a dualistic perspective on trust: trust in a specific person or organization (a moral and volitional agent) and trust in a specific technology or IT artefact (lacking volition and moral agency).

    “Most IS research nowadays employs a dualistic perspective on trust (see Table 1).First, trust in a specific person or organization (a moral and volitional agent) (Lankton et al. 2015;McKnight et al. 2011), such as trust in an e-vendor (Gefen et al. 2003) or virtual team members (Robert et al. 2009).”

    From Trustworthy artificial intelligence (2021) · cites this paper as Lankton et al. 2015

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Authors
Marshall University, Lankton, N., McKnight, D. H., Michigan State University, Tripp, J., & Baylor University
Affiliations
  • Marshall University (US)
  • Michigan State University (US)
  • Baylor University (US)
ORCID
Venue
Journal of the Association for Information Systems
Publisher
Association for Information Systems
Published
2015-10
Volume
16
Issue
10
Pages
880-918
ISSN
1536-9323 (ISSN-L)
DOI
10.17705/1jais.00411
OpenAlex
W1854663754
Cited by
553
References
0
Citations by year
2026: 102 · 2025: 99 · 2024: 93 · 2023: 69 · 2022: 59 · 2021: 52 · 2020: 41 · 2019: 13 · 2018: 11 · 2017: 11 · 2016: 3
FWCI
13.67
Type
journal article
Language
en
Open access
Locations
  • Journal of the Association for Information Systems (publishedVersion)
  • Journal of the Association for Information Systems (submittedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
trust in technology, benevolence, integrity, helpfulness, reliability, social presence, social affordances

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