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Bulletin of the American Mathematical Society

The Bulletin publishes expository articles on contemporary mathematical research, written in a way that gives insight to mathematicians who may not be experts in the particular topic. The Bulletin also publishes reviews of selected books in mathematics and short articles in the Mathematical Perspectives section, both by invitation only.

ISSN 1088-9485 (online) ISSN 0273-0979 (print)

The 2020 MCQ for Bulletin of the American Mathematical Society is 0.84.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.

 

Mathematics, word problems, common sense, and artificial intelligence
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by Ernest Davis
Bull. Amer. Math. Soc. 61 (2024), 287-303
DOI: https://doi.org/10.1090/bull/1828
Published electronically: February 15, 2024

Abstract:

The paper discusses the capacities and limitations of current artificial intelligence (AI) technology to solve word problems that combine elementary mathematics with commonsense reasoning. No existing AI systems can solve these reliably. We review three approaches that have been developed, using AI natural language technology: outputting the answer directly, outputting a computer program that solves the problem, and outputting a formalized representation that can be input to an automated theorem verifier. We review some benchmarks that have been developed to evaluate these systems and some experimental studies. We discuss the limitations of the existing technology at solving these kinds of problems. We argue that it is not clear whether these kinds of limitations will be important in developing AI technology for pure mathematical research, but that they will be important in applications of mathematics, and may well be important in developing programs capable of reading and understanding mathematical content written by humans.
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Bibliographic Information
  • Ernest Davis
  • Affiliation: Department of Computer Science, New York University, New York, New York 10012
  • MR Author ID: 242245
  • ORCID: 0000-0003-4812-817X
  • Email: davise@cs.nyu.edu
  • Published electronically: February 15, 2024
  • © Copyright 2024 by the author
  • Journal: Bull. Amer. Math. Soc. 61 (2024), 287-303
  • MSC (2020): Primary 68V99
  • DOI: https://doi.org/10.1090/bull/1828
  • MathSciNet review: 4726993