Philosophy of Probability and Artificial Intelligence

Catalog description

This advanced course explores the philosophical foundations of probability and their significance for contemporary artificial intelligence and machine learning. Students examine major interpretations of probability - including frequentist, Bayesian, propensity, and epistemic approaches - and analyze how these frameworks inform reasoning under uncertainty, inference, explanation, and decision-making. The course focuses on the philosophical foundations of probability and the conceptual complexities of probabilistic AI modeling. Philosophical questions include how AI systems represent uncertainty, what it means for an algorithm to update beliefs, and how probabilistic outputs should be interpreted and evaluated. Students develop the ability to critically assess probabilistic reasoning in AI systems and apply philosophical analysis to contemporary technological challenges. While this course engages with a highly technical subject matter, only a solid foundation in high-school level algebra is assumed. Prerequisite: sophomore standing. One of the following recommended: CS 101 , CT 100 , MTH 150 , or STAT 145 , PHL 101 . Offered Annually.