# Bayesian artificial brain with ChatGPT

arXiv: https://arxiv.org/abs/2308.14732 · HTML: https://mlsanity.com/paper/2308.14732/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 5 references that are in the map.
- First posted on arXiv 28 Aug 2023.

## Built on by (most cited first, 1 of 1)

- [Large Language Models Don't Make Sense of Word Problems. A Scoping Review from a Mathematics Education Perspective](https://mlsanity.com/paper/2506.24006/) (2025)

## Abstract (arXiv)

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.