Stevan Harnad: AI's Symbol Grounding Problem

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Aug 31, 2023

Guest Stevan Harnad, professor of psychology and cognitive science, discusses the Symbol Grounding Problem in AI. They explore category formation, non-linguistic category learning, and the limitations of current AI models. The episode also touches on Alan Turing's motivation, the easy and hard problems of AI, multimodal systems, and categorical perception in machine learning models and humans.

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Introduction

00:00 • 5min

Exploring the Interviewee's Background, Journal Editorship, and the Chinese Room Article

05:21 • 3min

Usenet, Open Access, and the Symbol Grounding Problem

08:44 • 12min

Category Formation and Sensory Experience

20:27 • 33min

Alan Turing's Motivation and Human Capacity Modeling

53:23 • 12min

The Easy Problem and the Hard Problem of AI

01:05:49 • 30min

Multimodal Systems and Compositional Understanding

01:35:28 • 17min

Categorical Perception in Machine Learning Models and Humans

01:52:37 • 4min

Final Questions and Closing Remarks

01:56:13 • 2min

In episode 88 of The Gradient Podcast, Daniel Bashir speaks to Professor Stevan Harnad.

Stevan Harnad is professor of psychology and cognitive science at Université du Québec à Montréal, adjunct professor of cognitive science at McGill University, and professor emeritus of cognitive science at the University of Southampton. His research is on category learning, categorical perception, symbol grounding, the evolution of language, and animal and human sentience (otherwise known as “consciousness”). He is also an advocate for open access and an activist for animal rights.

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Outline:

* (00:00) Intro

* (05:20) Professor Harnad’s background: interests in cognitive psychobiology, editing Behavioral and Brain Sciences

* (07:40) John Searle submits the Chinese Room article

* (09:20) Early reactions to Searle and Prof. Harnad’s role

* (13:38) The core of Searle’s argument and the generator of the Symbol Grounding Problem, “strong AI”

* (19:00) Ways to ground symbols

* (20:26) The acquisition of categories

* (25:00) Pantomiming, non-linguistic category formation

* (27:45) Mathematics, abstraction, and grounding

* (36:20) Symbol manipulation and interpretation language

* (40:40) On the Whorf Hypothesis

* (48:39) Defining “grounding” and introducing the “T3” Turing Test

* (53:22) Turing’s concerns, AI and reverse-engineering cognition

* (59:25) Other Minds, T4 and zombies

* (1:05:48) Degrees of freedom in solutions to the Turing Test, the easy and hard problems of cognition

* (1:14:33) Over-interepretation of AI systems’ behavior, sentience concerns, T3 and evidence sentience

* (1:24:35) Prof. Harnad’s commentary on claims in The Vector Grounding Problem

* (1:28:05) RLHF and grounding, LLMs’ (ungrounded) capabilities, syntactic structure and propositions

* (1:35:30) Multimodal AI systems (image-text and robotic) and grounding, compositionality

* (1:42:50) Chomsky’s Universal Grammar, LLMs and T2

* (1:50:55) T3 and cognitive simulation

* (1:57:34) Outro

Links:

* Professor Harnad’s webpage and skywritings

* Papers:

* Category Induction and Representation

* Categorical Perception

* From Sensorimotor Categories to Grounded Symbols

* Minds, machines and Searle 2

* The Latent Structure of Dictionaries

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