Document Type
Article
Publication Date
1-2020
Keywords
Low-prevalence effect, Facial identification, Imposter identification, Performance feedback, Receiver operating characteristic curves
Abstract
In many real-world settings, individuals rarely present another person’s ID, which increases the likelihood that a screener will fail to detect it. Three experiments examined how within-person variability (i.e., differences between two images of the same person) and feedback may have influenced criterion shifting, thought to be one of the sources of the low-prevalence effect (LPE). Participants made identity judgments of a target face and an ID under either high, medium, or low mismatch prevalence. Feedback appeared after every trial, only error trials, or no trials. Experiment 1 used two controlled images taken on the same day. Experiment 2 used two controlled images taken at least 6 months apart. Experiment 3 used one controlled and one ambient image taken at least 1 year apart. Importantly, receiver operating characteristic curves revealed that feedback and greater within-person variability exacerbated the LPE by affecting both criterion and discriminability. These results carry implications for many real-world settings, such as border crossings and airports, where identity screening plays a major role in securing public safety.
Digital Object Identifier (DOI)
https://doi.org/10.1186/s41235-019-0204-1
Repository Citation
Weatherford, Dawn R.; Erickson, William B.; Thomas, Jasmyne; Walker, Mary E.; and Schein, Barret, "You Shall Not Pass: How Facial Variability and Feedback Affect the Detection of Low-prevalence Fake IDs" (2020). Psychology Faculty Publications. 17.
https://digitalcommons.tamusa.edu/psyc_faculty/17
Comments
This is the published version of:
Weatherford, D.R., Erickson, W.B., Thomas, J. et al. You shall not pass: how facial variability and feedback affect the detection of low-prevalence fake IDs. Cognitive Research: Principles and Implications 5, 3 (2020). https://doi.org/10.1186/s41235-019-0204-1
© The Author(s). 2020 Open Access
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