Detecting recollection: Human evaluators can successfully assess the veracity of others' memories

Humans have the highly adaptive ability to learn from others' memories. However, because memories are prone to errors, in order for others' memories to be a valuable source of information, we need to assess their veracity. Previous studies have shown that linguistic information conveyed in...

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Bibliographic Details
Published in:	Proceedings of the National Academy of Sciences - PNAS Vol. 121; no. 22; p. e2310979121
Main Authors:	Gamoran, Avi, Lieberman, Lilach, Gilead, Michael, Dobbins, Ian G, Sadeh, Talya
Format:	Journal Article
Language:	English
Published:	United States National Academy of Sciences 28-05-2024
Subjects:	Adult False alarms Female Humans Machine Learning Male Memory - physiology Mental Recall - physiology Recognition, Psychology - physiology Young Adult memory justifications language machine learning recognition memory
Online Access:	Get full text
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Summary:	Humans have the highly adaptive ability to learn from others' memories. However, because memories are prone to errors, in order for others' memories to be a valuable source of information, we need to assess their veracity. Previous studies have shown that linguistic information conveyed in self-reported justifications can be used to train a machine-learner to distinguish true from false memories. But can humans also perform this task, and if so, do they do so in the same way the machine-learner does? Participants were presented with justifications corresponding to Hits and False Alarms and were asked to directly assess whether the witness's recognition was correct or incorrect. In addition, participants assessed justifications' recollective qualities: their vividness, specificity, and the degree of confidence they conveyed. Results show that human evaluators can discriminate Hits from False Alarms above chance levels, based on the justifications provided per item. Their performance was on par with the machine learner. Furthermore, through assessment of the perceived recollective qualities of justifications, participants were able to glean more information from the justifications than they used in their own direct decisions and than the machine learner did.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0027-8424 1091-6490
DOI:	10.1073/pnas.2310979121