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Technology, Humanness, and Trust: Rethinking Trust in Technology
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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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“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“Specifically, the literature on trust in technology has distinguished between human-like trust constructs and systemlike trust constructs (Lankton et al., 2015).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as Lankton et al., 2015
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“Within this stream of research, the social presence theory (Short et al., 1976) claims that a technology's attributes affect individuals' perception of technology as more human-like than systemlike (Lankton et al., 2015).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as Lankton et al., 2015
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In the citing paper
“Generally, when users are dealing with algorithms that share human-like characteristics, their trust beliefs are triggered by features of interpersonal trust: benevolence, competence and ability , and integrity (Mayer et al., 1995; Lankton et al. 2015; Gefen et al., 2003).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as Lankton et al. 2015
In the citing paper
“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
In the citing paper
“To understand trust relationships in such scenarios, two research streams emerged that either adapted the concept of interpersonal trust to conceptualize trust in human-like IT artifacts (Lankton et al. 2015), or revised the concept of trust in technology to account for automation technology and autonomous systems (J.D. Lee and See 2004).”
From Trustworthy artificial intelligence (2021) · cites this paper as Lankton et al. 2015
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Graichen, L., & Graichen, M. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108189 · Cited by 15
Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence
Toussaint, W., & Ding, A. Y. (2020) · IEEE International Conference on Cognitive Machine Intelligence (CogMI) · doi:10.1109/cogmi50398.2020.00030 · Cited by 19
Nissen, A., & Jahn, K. (2021) · Hawaii International Conference on System Sciences · doi:10.24251/hicss.2021.043 · Cited by 9
Mooshammer, S., & Etzrodt, K. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-94890-0_11 · Cited by 13
Game-inspired Pedagogical Conversational Agents: A Systematic Literature Review
Braunschweig, T. U., Khosrawi-Rad, B., Grogorick, L., Braunschweig, T. U., Robra-Bissantz, S., & Braunschweig, T. U. (2023) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00187 · Cited by 17
Trust and Human Factors in the Design of Healthcare Technology
Borsci, S., Buckle, P., Walne, S., & Salanitri, D. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-96071-5_21 · Cited by 13
Tasks Over Traits: User Perception of Humanlike Features in Goal-Oriented Chatbots
Haresamudram, K., van As, N., & Larsson, S. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2470311 · Cited by 17
Dis/Trust and data-driven technologies
Dueñas-Cid, D., & Calzati, S. (2023) · Internet Policy Review · doi:10.14763/2023.4.1727 · Cited by 18
Aalberg, A. L., Holen, S. M., Kongsvik, T., & Wahl, A. M. (2024) · Safety Science · doi:10.1016/j.ssci.2024.106426 · Cited by 17
Wang, M., Kang, Y., Deng, B., & Lan, X. (2024) · Telematics and Informatics · doi:10.1016/j.tele.2024.102193 · Cited by 17
Human vs. AI: Does AI learning assistant enhance students’ innovation behavior?
Luo, L., Hu, J., Zheng, Y., & Li, C. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13474-z · Cited by 19
Anke, J., & Richter, D. (2023) · HMD Praxis der Wirtschaftsinformatik · doi:10.1365/s40702-023-00965-1 · Cited by 12
The Role of Psychology in Understanding Online Trust
Jones, H. S., & Moncur, W. (2018) · Advances in digital crime, forensics, and cyber terrorism book series · doi:10.4018/978-1-5225-4053-3.ch007 · Cited by 12
van Leeuwen, A., & Rummel, N. (2022) · Unterrichtswissenschaft · doi:10.1007/s42010-022-00156-9 · Cited by 12
The second extended model of consumer trust in cryptocurrency payments, CRYPTOTRUST 2
Zarifis, A., & Fu, S. (2024) · Frontiers in Blockchain · doi:10.3389/fbloc.2024.1220031 · Cited by 11
Thakur, R., & John, J. (2024) · International Journal of Electronic Commerce · doi:10.1080/10864415.2024.2401950 · Cited by 15
Chew, E. A. L., Teo, S. H., Tang, W. E., Ng, D. W. L., Koh, G. C., & Teo, V. H. Y. (2023) · JMIR Human Factors · doi:10.2196/36072 · Cited by 12
The Importance of the Interface between Humans and Computers on the Effectiveness of eHRM
Johnson, R. D., Lukaszewski, K. M., Stone, D. L., & Tech, V. (2017) · AIS Transactions on Human-Computer Interaction · doi:10.17705/1thci.00087 · Cited by 13
Wut, T. M., Lee, S. W., Xu, J. B., & Kwok, M. L. J. (2025) · Informatics · doi:10.3390/informatics12030091 · Cited by 11
All risks ain't the same – A risk facets perspective on AI-based decision support systems
Strunk, J., Nissen, A., & Smolnik, S. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114557 · Cited by 10
Talking body: the effect of body and voice anthropomorphism on perception of social agents
Haresamudram, K., Torre, I., Behling, M., Wagner, C., & Larsson, S. (2024) · Frontiers in Robotics and AI · doi:10.3389/frobt.2024.1456613 · Cited by 12
Romanov, B., Dueñas-Cid, D., & Leets, P. (2025) · Government Information Quarterly · doi:10.1016/j.giq.2025.102068 · Cited by 23
Chang, R.-C., Natalie, R., Xu, W., Yap, J. Z. F., & Guo, A. (2025) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3663547.3746319 · Cited by 21
Understanding the Necessary Conditions of Multi-Source Trust Transfer in Artificial Intelligence
Renner, M., Lins, S., Söllner, M., Thiebes, S., & Sunyaev, A. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.717 · Cited by 10
The Alchemy of Trust: The Creative Act of Designing Trustworthy Socio-Technical Systems
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The Importance of an Ethical Framework for Trust Calibration in AI
Schmid, A., & Wiesche, M. (2023) · IEEE Intelligent Systems · doi:10.1109/mis.2023.3320443 · Cited by 13
Influence of Media Capabilities on Trust in the Sharing Economy
Harrison, A., Mirsadikov, A., & Luu, T. (. (2023) · Journal of Management Information Systems · doi:10.1080/07421222.2023.2229118 · Cited by 10
“Prior research has suggested that research should explore the relationship between trust and information technologies as potential moderators of trust in the SE [64] and has proposed that the characteristics of technology could moderate the impacts of the trust constructs [9, 51].”
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Plohl, N., Mlakar, I., Aquilino, L., Bisconti, P., & Smrke, U. (2025) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2384821 · Cited by 9
Chatterjee, R., George, S. R., Verma, J. S., Heggde, G. S., & Gadhavi, D. D. (2025) · Journal of Service Theory and Practice · doi:10.1108/jstp-08-2024-0258 · Cited by 9
Technology humanness, trust and e-government adoption
Carter, L. D., & Liu, D. (2018) · University of Technology, Sydney eBooks · doi:10.5130/acis2018.cp · Cited by 9
Shim, H., Cho, J., & Sung, Y. H. (2024) · Asian Communication Research · doi:10.20879/acr.2024.21.019 · Cited by 11
Müller, L. S., Meeßen, S. M., Thielsch, M. T., Nohe, C., Riehle, D. M., & Hertel, G. (2020) · Mensch und Computer (MuC) · doi:10.1145/3404983.3405515 · Cited by 9
Mousa, H. A. A., Mousa, M., Chaouali, W., Hammami, S. M., McKnight, H., & Danks, N. P. (2021) · International Journal of Retail & Distribution Management · doi:10.1108/ijrdm-04-2021-0159 · Cited by 12
Lee, B. S., & Cho, E. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2041910 · Cited by 9
Privacy and Trust in eHealth: A Fuzzy Linguistic Solution for Calculating the Merit of Service
Ruotsalainen, P. S., Blobel, B. G. M. E., & Pohjolainen, S. A. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12050657 · Cited by 9
Riar, M., Weber, M., Ebert, J., & Morschheuser, B. (2025) · Information Systems Frontiers · doi:10.1007/s10796-024-10573-z · Cited by 8
Kim, T., Lee, O.-K. D., & Kang, J. (2025) · Industrial Management & Data Systems · doi:10.1108/imds-04-2024-0329 · Cited by 15
Raza, S. H., Norin, U., Ogadimma, E. C., Zaman, U., Shah, A. A., Khan, S., Alkahtani, H. K., Alkhowaiter, M., & Khan, S. U. (2025) · BMC Public Health · doi:10.1186/s12889-025-22082-y · Cited by 8
Big brother is watching you: Examining truck drivers’ acceptance of road-facing dashcams
Gruchmann, T., & Jazairy, A. (2025) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2025.03.015 · Cited by 9
Leusmann, J., Villa, S., Berberoglu, B., Wang, C., & Mayer, S. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713087 · Cited by 10
In Technology We Trust! But Should We?
Sica, A., & Sætra, H. S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-35599-8_19 · Cited by 9
A functional framework for multisensory and interactive mediated social touch experiences
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Acceptance of Biometric Authentication Security Technology on Mobile Devices
Malatji, W. R., Eck, R. V., & Zuva, T. (2020) · International Multidisciplinary Information Technology and Engineering Conference (IMITEC) · doi:10.1109/imitec50163.2020.9334082 · Cited by 8
What HMC Teaches Us About Authenticity
Etzrodt, K., Kim, J., van der Goot, M. J., Prahl, A., Choi, M., Craig, M. J. A., Dehnert, M., Engesser, S., Frehmann, K., Grande, L., et al. (2024) · Human-Machine Communication · doi:10.30658/hmc.8.11 · Cited by 8
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Högström, J., Paakkari, A., Nilsberth, M., & Slotte, A. (2024) · Learning Media and Technology · doi:10.1080/17439884.2024.2436566 · Cited by 7
Beyond the monotonic: Enhancing human-robot interaction through affective communication
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Fernández, M. A., Astobiza, A. M., & Lozano, R. O. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11306-7 · Cited by 10
Measuring Social Trust in AI: How Institutions Shape the Usage Intention of AI‐Based Technologies
Amir, S., Luk, S. C. Y., Saha, S., Tsyrulneva, I., & Teo, M. T. L. (2025) · Human Behavior and Emerging Technologies · doi:10.1155/hbe2/4084384 · Cited by 10
Obadă, D.-R., Grădinaru, C., & Grădinaru, I.-A. (2026) · Frontiers in Communication · doi:10.3389/fcomm.2025.1722464 · Cited by 14
Giannitsas, D., Sun, R., & Baptista, J. (2026) · Information and Organization · doi:10.1016/j.infoandorg.2026.100609 · Cited by 11
Ghasemaghaei, M. (2026) · Journal of Management Information Systems · doi:10.1080/07421222.2025.2602397 · Cited by 10
Towards detecting the level of trust in the skills of a virtual assistant from the user’s speech
Gauder, L., Pepino, L., Riera, P., Brussino, S., Vidal, J., Gravano, A., & Ferrer, L. (2023) · Computer Speech & Language · doi:10.1016/j.csl.2023.101487 · Cited by 7
Trust Development and Explainability: A Longitudinal Study with a Personalized Assistive System
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Farmer’s acceptance towards sustainable farming technology
Sa’ari, E. A. (2017) · International Journal of ADVANCED AND APPLIED SCIENCES · doi:10.21833/ijaas.2017.012.038 · Cited by 7
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Riedl, R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108770880.005 · Cited by 6
The issue of user trust in decentralized applications running on blockchain platforms
Bracamonte, V., & Okada, H. (2017) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas.2017.8318975 · Cited by 7
How Learners’ Trust Changes in Generative AI Over a Semester of Undergraduate CoursesPreprint
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Transactive memory systems in superteams: the effect of an intelligent assistant in virtual teams
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"I can feel the risks by looking at the robot face": Communicating Risk through a Physical Agent
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Affect and information technology use: the impact of state affect on cognitions and IT use
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The Six Ways to Build Trust and Reduce Privacy Concern in a Central Bank Digital Currency (CBDC)
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Factors Influencing Trust in WhatsApp: A Cross-Cultural Study
Beltrão, G., & Sousa, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90238-4_35 · Cited by 7
Salamoun, R., Karam, C. M., & Abdallah, C. (2022) · Information Technology and People · doi:10.1108/itp-06-2020-0434 · Cited by 8
The Effects of Digitally Delivered Nudges in a Corporate Wellness Program
Babar, Y., Curley, S. P., Ke, Z., De, L., & Sheffler, Z. J. (2023) · Journal of the Association for Information Systems · doi:10.17705/1jais.00783 · Cited by 6
Tenzin, S., McGill, T. J., & Dixon, M. W. (2024) · Journal of Global Information Technology Management · doi:10.1080/1097198x.2023.2297634 · Cited by 13
Wang, T., Wang, Y., Wen, Y., & Wang, C. (2024) · Journal of Media Economics · doi:10.1080/08997764.2024.2360394 · Cited by 9
Alharbi, S. T. (2017) · International Journal of Information Technology and Computer Science · doi:10.5815/ijitcs.2017.11.02 · Cited by 6
Metadata
- 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)
- 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)
- 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
- bronze
- doi.org
- 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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