The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Overtrust of robots in emergency evacuation scenarios
Abstract
Robots have the potential to save lives in emergency scenarios, but could have an equally disastrous effect if participants overtrust them. To explore this concept, we performed an experiment where a participant interacts with a robot in a non-emergency task to experience its behavior and then chooses whether to follow the robot's instructions in an emergency or not. Artificial smoke and fire alarms were used to add a sense of urgency. To our surprise, all 26 participants followed the robot in the emergency, despite half observing the same robot perform poorly in a navigation guidance task just minutes before. We performed additional exploratory studies investigating different failure modes. Even when the robot pointed to a dark room with no discernible exit the majority of people did not choose to safely exit the way they entered.
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“Poor trust calibration sometimes causes serious safety issues [3, 4].”
From Adaptive trust calibration for human-AI collaboration (2020) · cites this paper as [4]
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Metadata
- Authors
- Robinette, P., Li, W., Allen, R., Howard, A. M., & Wagner, A. R.
- Affiliations
- Georgia Institute of Technology (US)
- Venue
- 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
- Publisher
- IEEE
- Published
- 2016-03
- Pages
- 101-108
- OpenAlex
- W4254148040
- Cited by
- 468
- References
- 16
- Citations by year
- 2026: 33 · 2025: 59 · 2024: 68 · 2023: 52 · 2022: 71 · 2021: 53 · 2020: 46 · 2019: 38 · 2018: 27 · 2017: 17 · 2016: 4
- FWCI
- 48.41
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
- Funders
- Research Institute, Georgia Institute of Technology
- Georgia Institute of Technology
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Safety Research › Evacuation and Crowd Dynamics
- Keywords
- trust in robots, emergency evacuation, human-robot interaction, guidance and navigation, emergency response
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 ›
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