Can a Machine Understand?: ChatGPT, Knowledge, and the Nature of Understanding – Prof. Tomás Bogardus
Prof. Tomás Bogardus asks whether a machine can truly understand by unpacking how large language models like ChatGPT function and arguing that genuine knowledge requires rational insight and responsibility to truth that go beyond statistical text prediction.
This lecture was given on November 17th, 2025, at University of Georgia.
For more information on upcoming events, visit us at thomisticinstitute.org/upcoming-events.
About the Speakers:
Tomás Bogardus earned his BS in biology at UC San Diego, his MA in philosophy at Biola University, and his PhD in philosophy at the University of Texas at Austin. He works mainly in metaphysics and epistemology, and is most interested in the mind-body problem, the rationality of religious belief, and the nature of gender.
Keywords: Artificial Intelligence, Insight, Knowledge versus Prediction, Large Language Models, Next-Token Prediction Models, Pattern Recognition and Meaning, Statistical Language Modeling, Truth and Responsibility, Understanding
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Prof. Tomás Bogardus asks whether a machine can truly understand by unpacking how large language models like ChatGPT function and arguing that genuine knowledge requires rational insight and responsibility to truth that go beyond statistical text prediction.
This lecture was given on November 17th, 2025, at University of Georgia.
For more information on upcoming events, visit us at thomisticinstitute.org/upcoming-events.
About the Speakers:
Tomás Bogardus earned his BS in biology at UC San Diego, his MA in philosophy at Biola University, and his PhD in philosophy at the University of Texas at Austin. He works mainly in metaphysics and epistemology, and is most interested in the mind-body problem, the rationality of religious belief, and the nature of gender.
Keywords: Artificial Intelligence, Insight, Knowledge versus Prediction, Large Language Models, Next-Token Prediction Models, Pattern Recognition and Meaning, Statistical Language Modeling, Truth and Responsibility, Understanding
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