The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Can Semi-Anthropomorphism Influence Trust and Compliance?: Exploring Image Use in App Interfaces
Abstract
Relying on automated suggestions from technology to make decisions has become a part of our everyday life. Most existing research examines trust in automation for high-risk domains as well as vast recommender systems for low-risk consumer use. This research aims to evaluate human trust in automated decision aids for low-risk everyday use, where one automated suggestion is presented and a few alternative options are available. In the current study, we investigate whether anthropomorphic imagery and information reliability can influence perceived trust of the automated decision aid. We report on results from 105 participants, which suggest that levels of semi-anthropomorphic imagery do not influence trust in the way that a full anthropomorphic image of a human might. Our work contributes to a deeper understanding of how to utilize design, specifically visual imagery, to appropriately calibrate trust in automated decision aids for everyday use.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Such behavioral measures include decision time, number of recommendation requests, and number of agreements with AI recommendations.
“Such measures include, but are not limited to measuring end-users' decision time [19,62], how many times end-users requested AI recommendation [52], and how many times they agreed with AI recommendations [7,23,58].”
From Being Trustworthy is Not Enough: How Untrustworthy Artificial Intelligence (AI) Can Deceive the End-Users and Gain Their Trust (2023) · cites this paper as [23]
Citations
Cites
Trust in Automation: Designing for Appropriate Reliance
Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3702 · Cited by 4,872
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 5×
“Most automated decision aids fall within the mid-range levels of the ten-level framework, meaning that the automation presents status information as well as one or more suggested actions but the human operator must decide which decision and action to take [10].”
BackgroundInfluentialUnderstanding Comics: The Invisible Art
MANNING, A. D. (1998) · IEEE Transactions on Professional Communication · doi:10.1109/tpc.1998.661632 · Cited by 3,126
Trust, control strategies and allocation of function in human-machine systems
LEE, J., & MORAY, N. (1992) · Ergonomics · doi:10.1080/00140139208967392 · Cited by 1,459
MUIR, B. M., & MORAY, N. (1996) · Ergonomics · doi:10.1080/00140139608964474 · Cited by 993
Pak, R., Fink, N. P., Price, M. M., Bass, B. M., & Sturre, L. (2012) · Ergonomics · doi:10.1080/00140139.2012.691554 · Cited by 204
Driver Acceptance of Unreliable Traffic Information in Familiar and Unfamiliar Settings
Kantowitz, B. H., Hanowski, R. J., & Kantowitz, S. C. (1997) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543831 · Cited by 113
The Man Who Lied to His Laptop: What We Can Learn About Ourselves from Our Machines
Nass, C., & Yen, C. T. (2012) · Medical Entomology and Zoology · Cited by 64
Madhavan, P., & Phillips, R. R. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2009.10.005 · Cited by 59
Flagged first, then by citations
Research works printed but not linked: 3
- Mark A. Hamilton and Kristine L. Nowak. 2009. The role of realism and anthropomorphism in the selection of avatars . In Proceedings of the 12th Annual International Workshop on Presence, The International Society for Presence Research, 1--12 . Mark A. Hamilton and Kristine L. Nowak. 2009. The role of realism and anthropomorphism in the selection of avatars. In Proceedings of the 12th Annual International Workshop on Presence, The International Society for Presence Research, 1--12.
- 10.1518/hfes.46.1.50.30392 · DOI · Paper page
- 10.5555/236605 · DOI
Cited by
Sorted by citations
How to Evaluate Trust in AI-Assisted Decision Making? A Survey of Empirical Methodologies
Vereschak, O., Bailly, G., & Caramiaux, B. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3476068 · Cited by 229
Banovic, N., Yang, Z., Ramesh, A., & Liu, A. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579460 · Cited by 55
Metadata
- Authors
- Gruber, D., Aune, A., & Koutstaal, W.
- Affiliations
- University of Minnesota (US)
- ORCID
- Koutstaal, Wilma
- Venue
- Proceedings of the Technology, Mind, and Society
- Publisher
- ACM
- Published
- 2018-04-05
- Pages
- 1-6
- OpenAlex
- W2790831167
- Cited by
- 8
- References
- 10
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 1 · 2019: 2
- FWCI
- 1.34
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Technology, Mind, and Society Conference (TechMindSociety) (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- anthropomorphic imagery, trust in automation, automated decision aids, compliance, information reliability, visual design, everyday technology use, recommender systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
