Why machines do not understand: A response to Søgaard

Archiv (2023)
  Copy   BIBTEX

Abstract

Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays insufficient attention to the difference between language as used by humans and the sequences of inert symbols which arise when language is stored on hard drives or in books in libraries.

Other Versions

No versions found

Links

PhilArchive

External links

  • This entry has no external links. Add one.
Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Do artificial intelligence systems understand?Carlos Blanco Pérez & Eduardo Garrido-Merchán - 2024 - Claridades. Revista de Filosofía 16 (1):171-205.
ChatGPT: Not Intelligent.Barry Smith - 2023 - Ai: From Robotics to Philosophy the Intelligent Robots of the Future – or Human Evolutionary Development Based on Ai Foundations.
Understanding programming languages.Raymond Turner - 2007 - Minds and Machines 17 (2):203-216.
Understanding the Language of God with the Language of the Universe.Ilyas Altuner - 2021 - Entelekya Logico-Metaphysical Review 5 (2):73-86.

Analytics

Added to PP
2023-10-04

Downloads
373 (#77,406)

6 months
83 (#73,593)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

Jobst Landgrebe
State University of New York (SUNY)
Barry Smith
University at Buffalo

Citations of this work

No citations found.

Add more citations

References found in this work

On Computable Numbers, with an Application to the Entscheidungsproblem.Alan Turing - 1936 - Proceedings of the London Mathematical Society 42 (1):230-265.
Minds, Brains, and Programs.John Searle - 2003 - In John Heil (ed.), Philosophy of Mind: A Guide and Anthology. New York: Oxford University Press.
Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.

Add more references