Understanding the Impact of Time Pressure and Automation Support in a Visual Search Task
Abstract
Objective: To understand the impact of time pressure and automated decision support systems (DSS) in a simulated medical visual search task. Background: Time pressure usually impairs manual performance in visual search tasks, but DSS support might neutralize this negative effect. Moreover, understanding the impact of time pressure and DSS support seems relevant for many real-world applications of visual search. Method: We used a visual search paradigm where participants had to search for target letters in a simulated medical image. Participants performed the task either manually or with support of a highly reliable DSS. Time pressure was varied within-subjects by either a trialwise time–pressure manipulation (Experiment 1) or a blockwise manipulation (Experiment 2). Performance was assessed based on signal detection measures. To further analyze visual search behavior, a mouse-over approach was used. Results: In both experiments, results showed impaired sensitivity under high compared to low time pressure in the manual condition, but no negative effect of time pressure when working with a highly reliable DSS. Moreover, participants searched less under time pressure and when receiving DSS support, indicating participants followed the automation without thoroughly checking recommendations. However, the human-DSS team’s sensitivity was always worse than that of the DSS alone, independent of the strength of time pressure. Conclusion: Negative effects of time pressure can be ameliorated when receiving support by a DSS, but joint overall performance remains below DSS-alone performance. Application: Highly reliable DSS seem capable of ameliorating the negative impact of time pressure in complex detection tasks.
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Significant time pressure may undermine various conditions for effectiveness.
“Significant time pressure may undermine various conditions for effectiveness [65].”
From On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives (2024) · cites this paper as [65]
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“A similar issue has been observed in human-machine interaction research (Boskemper et al., 2022; Rieger & Manzey, 2024).”
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“The images used in the X-ray task contained simulated 1/ f 3 noise, which resembles the power spectrum of mammograms (Burgess et al., 2001) and was used already in earlier research (e.g., Rieger et al., 2022; Rieger & Manzey, 2022; Sha et al., 2018).”
MethodSelf-citationCan increased automation transparency mitigate the effects of time pressure on automation use?
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“Additional evidence comes from research involving baggage screening stimuli (e.g., [42], [44], [45], and [46]) and other real-world visual search tasks such as (simulated) medical tasks (e.g., [47], [48], [49], and [50]).”
Self-citationExplaining AI weaknesses improves human–AI performance in a dynamic control task
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Self-citationThe Pop-Out Effect of Rarer Occurring Stimuli Shapes the Effectiveness of AI Explainability
Pithayarungsarit, P., Rieger, T., Onnasch, L., & Roesler, E. (2024) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813241261284 · Cited by 6 · see citing works
Self-citationThe impact of different distractions on outdoor visual search and object memory
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“This is in line with the finding that automated decision support diminishes people's search activities, although not leading to a complete lack of search (Rieger & Manzey, 2024).”
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“This phenomenon has been reported in studies on the effect of time pressure on HCI task performance [51] with potentially effective solutions, such as the use of assisted decision-making systems [52].”
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Self-citationTime Pressure Increases Automation Reliance in a Face Matching Task
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“This suboptimal performance has also been found in other areas of human-algorithm teaming research, where humans failed to reach the level of the automated DSS alone in a medical visual search task (Rieger & Manzey, 2022) and in a luggage screening task (Rice et al., 2008; Rieger & Manzey, 2020).”
InfluentialInfluence of Time Pressure on Successive Visual Searches
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“Similarly, Rieger and Manzey [26] examined participants’ performance in a simulated X-ray screening task, where they searched for a target letter under low and high time pressure.”
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“For instance, time pressure was found to decrease total task completion time (Slobounov et al., 2000) and increase dynamic visual search performance (Yu et al., 2015), but other studies found that time pressure dec-remented visual search performance (Rieger et al., 2021; Rieger & Manzey, 2022).”
ResultLikelihood Systems Can Improve Hit Rates in Low-Prevalence Visual Search Over Binary Systems
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“The task was similar to the uncovering paradigm in Rieger and Manzey (2024) and Rieger et al. (2021).”
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“…and AI reliance—with some studies reporting increased reliance under time pressure (Rice & Trafimow, 2012), others reporting reduced reliance (Rieger & Manzey, 2022), and still others finding no reliable effect (Zou et al., 2024)—because the direction of time pressure effects depends on the…”
Measuring trust in artificial intelligence with the N2pc component
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Self-citationAI Error Difficulty Modulates the Effectiveness of Explainability in Decision Support Systems
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“Within this restricted set, time pressure did not significantly reduce search time, contrary to prior studies reporting faster searches under time constraints (McCarley, 2009; Rieger et al., 2021; Rieger & Manzey, 2022; Slobounov et al., 2000).”
InfluentialFaster but Not Smarter? Temporal Constraints and User Compliance with AI Explanations
Shahu, A., Greinecker, N., & Wintersberger, P. (2026) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3772363.3798697
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Self-Generated Expectations of Hazard Prevalence Affect Virtual Search and Rescue
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“Time pressure reduces search accuracy, increasing miss rates and false positives (Rieger et al., 2021; Rieger & Manzey, 2024), suggesting that visual search becomes less thorough when cognitive resources (e.g., time for evidence accumulation) are constrained.”
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- Authors
- Rieger, T., & Manzey, D.
- Affiliations
- Technische Universität Berlin (DE)
- Corresponding author
- Rieger, Tobias
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2022-06-30
- Volume
- 66
- Issue
- 3
- Pages
- 770-786
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W4283730358
- Cited by
- 40
- References
- 50
- Citations by year
- 2026: 13 · 2025: 9 · 2024: 12 · 2023: 5 · 2022: 1
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Factors The Journal of the Human Factors and Ergonomics Society (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- time pressure, automated decision support system, visual search, medical image analysis, human-AI teaming, signal detection, detection sensitivity, trust in automation
- MeSH terms
- Time Pressure, Animals, Automation, Decision Making, Humans, Man-Machine Systems, Task Performance and Analysis, Mice
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