Why machines do not understand: A response to Søgaard

07/07/2023
by   Jobst Landgrebe, et al.
0

Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in this journal for a thesis of this sort, on the basis of the idea (1) that where there is semantics there is also understanding and (2) that 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 sogaard:2022. 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 of symbols which arise when language is stored on hard drives or in books in libraries.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/22/2022

Do Artificial Intelligence Systems Understand?

Are intelligent machines really intelligent? Is the underlying philosoph...
research
12/25/2017

Null Dynamical State Models of Human Cognitive Dysfunction

The hard problem in artificial intelligence asks how the shuffling of sy...
research
10/19/2020

Learning to Reconstruct and Segment 3D Objects

To endow machines with the ability to perceive the real-world in a three...
research
08/20/2023

A Review on Objective-Driven Artificial Intelligence

While advancing rapidly, Artificial Intelligence still falls short of hu...
research
11/01/2019

Weird Machines as Insecure Compilation

Weird machines—the computational models accessible by exploiting securit...

Please sign up or login with your details

Forgot password? Click here to reset