Welcome to EPOL 479: Machine Learning and Human Learning. This course examines the emerging synthesis between human cognition and artificial intelligence, drawing on philosophical frameworks from Hegel to contemporary cognitive science.
Course Overview
What does it mean for both humans and machines to “learn”? This course explores:
- The historical development of cognitive technologies
- Hegelian frameworks for understanding AI consciousness
- The master-bondsman dialectic in human-AI interaction
- Ethical implications of AI in education
Weekly Structure
Each week consists of a three-hour online seminar combining group discussion, lecture, and hands-on practice, with 10-minute breaks between hours. Seven seminars run across Term A; there is no class on Labor Day.
Learning objectives
- Understand the historical relationship between technology and learning
- Explore the phenomenology of AI-mediated learning experiences
- Develop critical frameworks for evaluating AI in educational contexts
- Practice synthesis of human and machine learning approaches
Course materials
Lecture notes and workshop materials from this course.
- Welcome to Machine Learning and Human Learning
- Introducing Hegel and The Concept of Experience (`Erfahrung’)
- Recognition and the Master-Servant Dialectic
- Attention
- Consciousness Through Historical Lens
- Alignment
- Bitter Lessons, Stochastic Parrots, Errant Agents: From Criticism to Immanent Critique?
- Hegel’s Revenge: The Return of the Grand Récit?
- EPOL 479 Fall 2026: references by week
- Learning Features Roadmap
- EPOL 479 Syllabus — Machine Learning and Human Learning
Reading list
- Unthought: The Power of the Cognitive Nonconscious
- The Phenomenology of Spirit