The Performance of Large Language Models on Quantitative and Verbal Ability Tests: Initial Evidence and Implications for Unproctored High-stakes Testing
Louis Hickman,
Patrick Damien Dunlop,
Jasper Leo Wolf
Abstract:Abstract. Unproctored assessments are widely used in pre-employment assessment. However, the recent emergence of widely accessible large language models (LLMs) poses challenges for unproctored personnel assessments, given that applicants may use them to artificially inflate their scores beyond their true abilities. This may be particularly concerning in cognitive ability testing, which is widely used and is less fakeable by humans than personality tests. Thus, this study compares the performance of LLMs on two… Show more
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