This paper aims to investigate the mathematical problem-solving capabilities of Chat Generative Pre-Trained Transformer (ChatGPT) in case of Bayesian reasoning. The study draws inspiration from Zhu & Gigerenzer's research in 2006, which posed the question: Can children reason the Bayesian way? In the pursuit of answering this question, a set of 10 Bayesian reasoning problems were presented. The results of their work revealed that children's ability to reason effectively using Bayesian principles is contingent upon a well-structured information representation. In this paper, we present the same set of 10 Bayesian reasoning problems to ChatGPT. Remarkably, the results demonstrate that ChatGPT provides the right solutions to all problems.

翻译：本文旨在探究Chat生成预训练变换器（ChatGPT）在贝叶斯推理场景下的数学问题解决能力。研究受Zhu与Gigerenzer 2006年研究成果的启发，该研究提出的核心问题是：儿童能否以贝叶斯方式进行推理？为解答此问题，该研究设计了10道贝叶斯推理问题。研究结果表明，儿童能否有效运用贝叶斯原理进行推理，取决于信息表征是否具有良好结构。本文向ChatGPT呈现了同样的10道贝叶斯推理问题，研究结果显示，ChatGPT成功为所有问题提供了正确解答。