Faking Resistance of Forced‐Choice and Single‐Statement Personality Measures: Stress‐Testing With Humans and Generative AI

ABSTRACT A major concern with personality assessment in high‐stakes settings is test‐takers misrepresenting (“faking”) their personalities. Although test developers have adopted difficult‐to‐fake forced‐choice (FC) formats, generative artificial intelligence (AI) now offers test‐takers a highly sophisticated “test‐coach,” and yet it is unclear how resilient FC formats are to faking by AI‐generated response sets. This investigation examined the faking resistance of single‐statement (SS), forced‐choice IRT (FC‐IRT), and forced‐choice CTT (FC‐CTT) versions of the HEXACO inventory. 219 Accounting/Finance professionals completed the three assessments under honest and applicant conditions, the latter for a role where Honesty‐Humility and Conscientiousness were target traits. Three frontier AI models were repeatedly prompted with analogous instructions to simulate AI‐assisted faking. We found that two AI models consistently outscored human test‐takers under applicant conditions across all formats. Among the human‐generated responses, the FC‐CTT format showed less inflation than FC‐IRT for Honesty‐Humility and better rank‐order stability in applicant conditions, but this pattern did not extend to Conscientiousness. Neither FC format demonstrated clear improvements in convergent or criterion‐related validity. Findings challenge the previous assumption that FC measurement approaches can fully mitigate human‐ or AI‐assisted faking.