ArticleFrontiers in human neuroscience2018
Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents.
Article in Frontiers in human neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
15 citing papers in PubMed.
- The Absent P3a. Performance Monitoring ERPs Differentiate Trust in Humans and Autonomous Systems.Psychophysiology · 2026Article
- A Neurocomputational Model of Observation-Based Decision Making with a Focus on Trust.Brain sciences · 2026Article
- Psychophysiological markers of trust in automation: insights from ERP responses in a modified flanker task.Cognitive research: principles and implications · 2026Article
- Matching embodied conversational agent appearance to message emotion enhances persuasion in eHealth.Scientific reports · 2025Article
- Judgments of Difficulty (JODs) While Observing an Automated System Support the Media Equation and Unique Agent Hypotheses.Human factors · 2025Article
- Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay.Frontiers in computational neuroscience · 2025Article
- Modeling trust and its dynamics from physiological signals and embedded measures for operational human-autonomy teaming.Frontiers in robotics and AI · 2025Article
- An EEG-network-metric based approach to real-time trust inference in human-autonomy teaming.Frontiers in neuroergonomics · 2025Article
- Brain mechanisms of automated conflict avoidance simulator supervision.Psychophysiology · 2023Article
- Article
- Misleading Robot Signals in a Classification Task Induce Cognitive Load as Measured by Theta Synchronization Between Frontal and Temporo-parietal Brain Regions.Frontiers in neuroergonomics · 2022Article
- In search of a Goldilocks zone for credible AI.Scientific reports · 2021Article
- Neural Correlates of Trust in Automation: Considerations and Generalizability Between Technology Domains.Frontiers in neuroergonomics · 2021Review
- Measurement of Trust in Automation: A Narrative Review and Reference Guide.Frontiers in psychology · 2021Review
- Grand Challenges in Neurotechnology and System Neuroergonomics.Frontiers in neuroergonomics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rise of increasingly complex artificial intelligence (AI), there is a need to design new methods to monitor AI in a transparent, human-aware manner. Decades of research have demonstrated that people, who are not aware of the exact performance levels of automated algorithms, often experience a mismatch in expectations. Consequently, they will often provide either too little or too much trust in an algorithm. Detecting such a mismatch in expectations, or
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.