← Search

Journal of Applied Psychology Vol. 108 No. 8 2023

How well can an AI chatbot infer personality? Examining psychometric properties of machine-inferred personality scores.

Jinyan Fan1; Tianjun Sun2; Jiayi Liu1; Teng Zhao1; Bo Zhang3; Zheng Chen4; Melissa Glorioso1; Elissa Hack5

1 Auburn University · 2 Kansas State University · 3 University of Illinois Urbana-Champaign · 4 University of South Florida St. Petersburg · 5 United States Air Force Academy

Abstract

= 61), we obtained test-retest data. Results indicated that machine-inferred personality scores (a) had overall acceptable reliability at both the domain and facet levels, (b) yielded a comparable factor structure to self-reported questionnaire-derived personality scores, (c) displayed good convergent validity but relatively poor discriminant validity (averaged convergent correlations = .48 vs. averaged machine-score correlations = .35 in the test sample), (d) showed low criterion-related validity, and (e) exhibited incremental validity over self-reported questionnaire-derived personality scores in some analyses. In addition, there was strong evidence for cross-sample generalizability of psychometric properties of machine scores. Theoretical implications, future research directions, and practical considerations are discussed. (PsycInfo Database Record

DOI
10.1037/apl0001082
Volume
108
Issue
8
Pages
1277-1299
Language
en
Sources
crossref openalex

Cite