The Psychonomic Society is pleased to announce that Emily N. Line & Sara Jaramillo have been honored with the 2025 Best Article Award for CR:PI. Congratulations on this well-deserved recognition. Read the paper here: bit.ly/4m85uqq #gocrpi @emily_line @_SaraJaramillo

Why are lineup rejections less diagnostic of innocence than suspect identifications are of guilt? Take a look at our preprint for insight on this all-too-common finding of the eyewitness id literature.

🚨 New preprint 🚨 Why should police video-record lineups? We videorecorded 1496 witnesses as they completed lineups. We coded the behaviors that these witnesses demonstrated and subjected the resulting data to machine learning analyses. Link and findings below!

🚨 New Publication in JEP: Applied @apajournals.bsky.social on eyewitness lineups authored alongside Andrew Smith and Gary Wells. www.researchgate.net/publication/...

How could AI be used to assess eyewitness identification accuracy? Andrew Smith, @nydia-ayala.bsky.social and @rying.bsky.social discuss three ways AI could prove useful! @officialsarmac.bsky.social #PsychLaw psycnet.apa.org/doi/10.1037/...

Check out our new paper on AI in eyewitness identification procedures now out in JARMAC. We outline three ways that AI can help sort accurate from inaccurate witnesses! @officialsarmac.bsky.social

Had a great experience presenting in the Eyewitness Identification session at @psychonomicsociety.bsky.social this past weekend. Looking forward to next year’s conference! 🙌🏻

🚨 New publication alert! In this paper, we find that the biased-lineup preference effect (or the finding that lay ppl rate IDs from biased lineups as more reliable than those from unbiased lineups) is driven by perceptual fluency. www.researchgate.net/publication/...

Wanted to share some really cool work! @nydia-ayala.bsky.social, Andrew Smith, & Gary Wells utilized machine learning to evaluate the utility of confidence, decision time, and the language of lineup justifications in the context of sequential & simultaneous lineups! See preprint below ⬇️