Ohio University Philosophy Forum Public Lecture: Dr. Cameron Buckner

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Thirty-First Annual Ohio University Philosophy Forum

Generative Deep Neural Networks as models of imagination, creativity, and planning”

A Public Lecture by Dr. Cameron Buckner, University of Florida

Thursday, November 5th, 2026, 4:00PM - 6:00PM, Scripps Hall 111

LECTURE ABSTRACT: In current debates in Artificial Intelligence, deep learning researchers have noted a historical kinship to the view in philosophy called "empiricism", which holds that abstract knowledge is produced by learning from experience. Critics of deep learning have in turn taken up mantle of philosophical "rationalism", which denies that the most sophisticated forms of human cognition can be derived from learning. The stakes of this philosophical debate are vividly illustrated in a disagreement between the empiricist David Hume and the rationalist Jerry Fodor over the role that the imagination plays in rational cognition, which centers on the question as to whether statistical learning procedures could be bootstrapped to perform distinctively human forms of creativity. Fodor alleged that empiricists are unable to explain how minds synthesize examples for use in reasoning, compose novel concepts from simpler concepts, engage in consequence-sensitive planning, or distinguish between causal and intentional relations amongst thoughts. Fodor applauds Hume for observing that rational cognition involves all these creative operations, but criticizes Hume’s delegation of these operations to the faculty of the imagination, because Hume never explains how learning could enable the imagination could perform all these feats. In this talk, I show how a variety of different "generative" deep learning architectures demonstrate how an empiricist imagination could perform such operations. I conclude with more general morals about the prospects for abstraction and reasoning in empiricist theorizing, about a mutually beneficial interaction between philosophy and computer science in this context, and about how philosophers and scientists should think about the creative potential of these new systems more generally.

SPEAKER BIO: Cameron Buckner is a Professor and the Donald F. Cronin Chair in the Humanities at the University of Florida. His research primarily concerns philosophical issues which arise in the study of non-human minds, especially animal cognition and artificial intelligence. He began his academic career in logic-based artificial intelligence. This research inspired an interest into the relationship between classical models of reasoning and the (usually very different) ways that humans and animals actually solve problems, which led him to the discipline of philosophy. He received a PhD in Philosophy at Indiana University in 2011 and an Alexander von Humboldt Postdoctoral Fellowship at Ruhr-University Bochum from 2011 to 2013. Representative publications include “Empiricism without Magic: Transformational Abstraction in Deep Convolutional Neural Networks” (2018, Synthese), and “Rational Inference: The Lowest Bounds” (2017, Philosophy and Phenomenological Research)—the latter of which won the American Philosophical Association's Article Prize for the period of 2016–2018. In 2024 he published a book with Oxford University Press that uses empiricist philosophy of mind (from figures such as Aristotle, Ibn Sina, John Locke, David Hume, William James, and Sophie de Grouchy) to understand recent advances in deep-neural-network-based artificial intelligence.