Testing After ChatGPT: Aggregate Change in Applicant Assessment Scores

ABSTRACT

The widespread adoption of large language model (LLM) chatbots has raised concerns about their potential misuse in high‐stakes employment contexts, including cheating on pre‐employment assessments. Although prior research demonstrates that LLMs can achieve desirable scores on cognitive and personality tests, little evidence exists regarding whether their availability has produced measurable score inflation in real‐world selection settings. The present study examines whether mean scores on commonly used pre‐employment assessments shifted following the public release of ChatGPT in November 2022. Using large archival samples of job applicants, we analyzed trends in scores on two cognitive assessments and one personality assessment. We also examined age as a moderator given evidence that younger individuals are more frequent users of LLM technologies. Regression and time‐trend analyses indicated statistically significant but practically negligible changes in assessment scores following ChatGPT's release. Across cognitive and personality measures, effect sizes were near zero and inconsistent in direction, providing no meaningful support for widespread LLM‐assisted cheating. Overall, results suggest that despite concerns about LLM misuse, there is currently little evidence of large‐scale score inflation in operational pre‐employment testing contexts.