Misuse of automated decision aids: complacency, automation bias and the impact of training experience
Integrity signals
Registry
Cites
Statistics
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?
Automation bias can lead users to follow a recommendation even if it is not the best choice, resulting in poor decision quality.
“Therefore, automation bias, including not seeking out confirmatory or contradictory information, can lead the user to follow a recommendation, even if it is not the best choice (Mosier and Skitka, 1999; Bahner et al., 2008), resulting in poor decision quality.”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bahner et al., 2008
Increasing users' awareness of system errors and weaknesses can decrease automation bias.
“In line with that, prior research showed that increasing the users’ awareness of system errors and weaknesses can decrease automation bias”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bahner et al., 2008
Automation bias can lead to system errors being overlooked and result in poor decision quality.
“Automation bias can lead to system errors being overlooked and thus result in poor decision quality”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bahner et al., 2008
Experiencing system failures can have a stronger impact on user behavior.
“Experiencing system failures can have a stronger impact on user behavior (Bahner et al., 2008).”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bahner et al., 2008
Previous studies demonstrated that decision makers who encountered system errors subsequently showed more verification behavior.
“Previous studies demonstrated that decision makers who encountered system errors subsequently showed more verification behavior (Manzey et al., 2006; Bahner et al., 2008).”
From Check the box! How to deal with automation bias in AI-based personnel selection (2023) · cites this paper as Bahner et al., 2008
The citation lists haven’t been fetched yet
References 34 · Cited by 279
- Authors
- Bahner, J. E., Hüper, A.-D., & Manzey, D.
- Affiliations
- Technische Universität Berlin (DE)
- Corresponding author
- Bahner, J. Elin
- ORCID
- Manzey, Dietrich
- Venue
- International Journal of Human-Computer Studies
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 66
- Issue
- 9
- Pages
- 688-699
- ISSN
- 1071-5819 (ISSN-L)
- OpenAlex
- W1999838653
- Cited by
- 279
- References
- 34
- Citations by year
- 2026: 28 · 2025: 22 · 2024: 20 · 2023: 26 · 2022: 9 · 2021: 13 · 2020: 20 · 2019: 27 · 2018: 13 · 2017: 16 · 2016: 17 · 2015: 11 · 2014: 14 · 2013: 12 · 2012: 9
- FWCI
- 9.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Studies (publishedVersion)
- Maritime Commons The Digital Repository of World Maritime University (World Maritime University) (submittedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Risk and Safety Analysis
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- complacency, automation bias, automated decision aids, commission errors, process control systems, operator training, human-automation interaction, fault diagnosis
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
