Great opportunity to work with great mentor!
16.12.2025 13:45
👍 1
🔁 0
💬 0
📌 0
Great opportunity to work with great mentor!
That's a wrap from Psychonomics 2025! Thanks to all who came to our symposium! Many thought provoking conversations!
Excited to present in the Artificial Intelligence and Human Memory symposium at 3:45 alongside some really great researchers. Hope y’all can drop by! #psynom2025 @psychonomicsociety.bsky.social
Off to Psychonomics! Presenting Friday at the 3:45 PM AI & Memory Symposium, along with other cool work by Ian Dobbins, Travis Seale-Carlisle, @chaddodson.bsky.social, @nydia-ayala.bsky.social, and Rachel Greenspan, and collaborators. Hope to see you this weekend!
Blue background and PS branding announcing the recipients, their institutions, and the title of the awarded paper.
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.
Many thanks to my coauthors for getting this massive project across the finish line: Andrew Smith,
@rying.bsky.social, Gary Wells, and Natalie Sommervold 🩵
It's been 20+ years since researchers recommended that police videorecord lineups. But no one has empirically tested the diagnostic value of these videos... until now.
Here, we provide a compelling case to mandate the videorecording of lineup procedures.
Finding #3:
Witnesses' lineup behavior can diagnose high-confidence mistaken identifications. When witnesses are highly confident but their behavior indicates a weak and disfluent recognition experience, the CJS system should doubt their accuracy.
Finding #2:
Not only did witness behaviors discriminate between accurate and inaccurate decisions, but they also improved classification performance over and above confidence and decision speed.
Finding #1:
Accurate witnesses behaved markedly different than inaccurate witnesses—a strong and fluent recognition experience implied accuracy and a weak and disfluent recognition experience implied inaccuracy.
🚨 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!
(3) Simultaneous lineups are superior to sequential lineups.
(2) that accurate witnesses’ justifications tended to reflect absolute language (e.g., “I recognized him”) and inaccurate witnesses’ justifications tended to reflect relative language (e.g., “He looks most like the person”).
We found that (1) using confidence, decision time, and the natural language witnesses expressed when justifying their lineup decision increased the potential to postdict accuracy
🚨 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
Repping Iowa State!
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/...
Paul Rudd!!!
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 ⬇️
