The talk given by Anna Ivanova & Kyle Mahowald in KUIS AI Talks on April 4, 2023.

Title: The Difference between Language and Thought

Abstract:
Today’s large language models (LLMs) routinely generate coherent, grammatical, and seemingly meaningful paragraphs of text. This achievement has led to speculation that these models are—or will soon become—“thinking machines”, capable of performing tasks that require abstract knowledge and reasoning. In this talk, I will argue that, when evaluating LLMs, we should distinguish between their formal linguistic competence—knowledge of linguistic rules and patterns—and functional linguistic competence—understanding and using language in the world. This distinction stems from modern neuroscience research, which shows that these skills recruit different mechanisms in the human brain. I will show that, although LLMs are close to mastering formal linguistic competence, they still fail at many functional competence tasks, which require drawing on various non-linguistic cognitive skills. Finally, I will discuss why we humans are so tempted to mistake fluent speech for fluent thought.

Short Bio:
Anna Ivanova is a Postdoctoral Associate at MIT Quest for Intelligence. She has a PhD from MIT’s Department of Brain and Cognitive Science, where she studied the neural mechanisms underlying language processing in humans. Today, Anna is examining the language-thought relationship in large language models, using her cognitive science training to identify similarities and differences between humans and machines.

Kyle Mahowald is an Assistant Professor of Linguistics at the University of Texas at Austin, where he is a PI in the UT Computational Linguistics group. He works broadly on the topic of human communication. Specifically, he is interested in what modern computational language models can tell us about human language, how linguistic efficiency can explain aspects of linguistic behavior and typology, and a variety of other topics in the cognitive science of language. He received a master's degree in linguistics from Oxford, completed his Ph.D. in Brain and Cognitive Science at MIT, and did his postdoctoral work in the Stanford Natural Language Processing group.