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Updated: Jan 23, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
Artificial Intelligence-based investigation of filler selection strategies
Dilhan Töredi1, Steven D Penrod1
1Department of Psychology, John Jay College of Criminal Justice, City University of New York.
Objective:
Lineup construction relies on matching fillers to the suspect's appearance or to the eyewitness's description of the perpetrator (match to description, MTD). Recent work shows that low (vs. high)-similarity fillers beyond MTD improve discriminability. We tested lineups constructed with differing suspect-filler (SF) similarity levels beyond MTD (low, moderate, high) against MTD only, varying exposure duration, culprit race, and innocent suspect-culprit resemblance (guilty-innocent [GI] similarity).
Hypotheses:
We expected the highest discriminability for low-SF similarity lineups, moderate next, MTD-only lower, and high lowest-alongside higher discriminability for long (cf. short) exposures, same-race (cf. cross-race) culprits, and low GI similarity (cf. high). We expected high-SF similarity to better protect high GI similarity innocents and low F-similarity to aid culprit identifications regardless of GI similarity. We also anticipated stronger benefits of low-SF similarity lineups for cross-race culprits and shorter exposures.
Method:
All lineups, except MTD only, were constructed using an artificial intelligence-driven, objective, and reproducible measure and varied by SF similarity. Participants (N = 2,644) recruited via Prolific watched four short or long videos (half with White, half with African American culprits), completed a distractor task, and made lineup identifications (culprit-present or culprit-absent) with confidence ratings.
Results:
Both low- and high-SF similarity lineups produced higher discriminability than MTD-only lineups. While low-SF similarity lineups enhanced guilty suspect detection, high-SF similarity lineups better protected innocent suspects. Furthermore, low-SF similarity lineups yielded the best identification accuracy, and high-SF similarity lineups yielded the best diagnosticity ratio. No interactions emerged.
Conclusions:
Using match-to-suspect beyond MTD-especially at the highest or lowest SF similarity-improves lineup performance regardless of factors outside the justice system's control. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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