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Title: Mind meets machine: Unravelling GPT-4's cognitive psychology

View PDF Abstract: Cognitive psychology delves on understanding perception, attention, memory, language, problem-solving, decision-making, and reasoning. Large language models (LLMs) are emerging as potent tools increasingly capable of performing human-level tasks. The recent development in the form of GPT-4 and its demonstrated success in tasks complex to humans exam and complex problems has led to an increased confidence in the LLMs to become perfect instruments of intelligence. Although GPT-4 report has shown performance on some cognitive psychology tasks, a comprehensive assessment of GPT-4, via the existing well-established datasets is required. In this study, we focus on the evaluation of GPT-4's performance on a set of cognitive psychology datasets such as CommonsenseQA, SuperGLUE, MATH and HANS. In doing so, we understand how GPT-4 processes and integrates cognitive psychology with contextual information, providing insight into the underlying cognitive processes that enable its ability to generate the responses. We show that GPT-4 exhibits a high level of accuracy in cognitive psychology tasks relative to the prior state-of-the-art models. Our results strengthen the already available assessments and confidence on GPT-4's cognitive psychology abilities. It has significant potential to revolutionize the field of AI, by enabling machines to bridge the gap between human and machine reasoning.

Submission history

From: Manmeet Singh [ view email ]
[v1] Mon, 20 Mar 2023 20:28:26 UTC (10,882 KB)
Wed, 12 Apr 2023 15:46:20 UTC (11,036 KB)
View a PDF of the paper titled Mind meets machine: Unravelling GPT-4's cognitive psychology, by Sifatkaur Dhingra and 4 other authors

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