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Generative AI and accuracy in the history of mathematics.

Authors :
Rowlett, Peter
Source :
British Journal for the History of Mathematics. Apr2024, Vol. 39 Issue 1, p64-69. 6p.
Publication Year :
2024

Abstract

Generative AI systems designed to produce text do so by drawing on inferences made from training data, which may mean they reproduce factual errors or biases contained in that data. This process is illustrated by querying ChatGPT with questions from a history of mathematics quiz designed to highlight the common occurrence of mathematical results being misattributed. ChatGPT's performance on a set of decades-old common misconceptions is mixed, illustrating the potential for these systems to reproduce and reinforce historical inaccuracies and misconceptions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26375451
Volume :
39
Issue :
1
Database :
Academic Search Index
Journal :
British Journal for the History of Mathematics
Publication Type :
Academic Journal
Accession number :
178213103
Full Text :
https://doi.org/10.1080/26375451.2024.2312789