On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs

Published: 16 Jan 2024, Last Modified: 11 Feb 2024ICLR 2024 oralEveryoneRevisionsBibTeX
Primary Area: societal considerations including fairness, safety, privacy
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Keywords: LLM, Benchmark, Evaluation, Psychometrics
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TL;DR: We propose a framework for evaluating the psychological portrayal of LLMs. We provide insights on the humanity of LLM leveraging our tool.
Abstract: Large Language Models (LLMs) have recently showcased their remarkable capacities, not only in natural language processing tasks but also across diverse domains such as clinical medicine, legal consultation, and education. LLMs become more than mere applications, evolving into assistants capable of addressing diverse user requests. This narrows the distinction between human beings and artificial intelligence agents, raising intriguing questions regarding the potential manifestation of personalities, temperaments, and emotions within LLMs. In this paper, we propose a framework, PPBench, for evaluating diverse psychological aspects of LLMs. Comprising thirteen scales commonly used in clinical psychology, PPBench further classifies these scales into four distinct categories: personality traits, interpersonal relationships, motivational tests, and emotional abilities. Our study examines five popular models, namely \texttt{text-davinci-003}, ChatGPT, GPT-4, LLaMA-2-7b, and LLaMA-2-13b. Additionally, we employ a jailbreak approach to bypass the safety alignment protocols and test the intrinsic natures of LLMs. We have made PPBench openly accessible via *\footnote{The link is hidden due to anonymity. For reviewers, please refer to the supplementary materials.}.
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Submission Number: 2500