Machine Learning and Human Learning

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

Tutor Lab

Open the Course 479 Tutor Lab to hold a conversation with the course tutor while its drafting process remains visible. Each reply appears alongside an initial draft, an internal critique, and a revision. You can change the tutor’s prompt stance and critic setting during the conversation, then compare what changes and what stays fixed.

The lab requires the class key distributed in the seminar. It does not require access to the project repository. Download your own transcript if you want to bring it into class discussion; the activity does not ask you to submit the conversation as research data.

Start with the Tutor Lab activity guide, then use the three reference deliberations to see how a draft, critique, and revision can diverge before you begin.

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.

Eight concepts are covered across the seven seminars: Recognition and Consciousness are taken together in Session 3. Sessions 2 to 6 each close with a self-assessed activity, five in all. Session 7 turns to the final synthesis report.

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