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Feb 05, 2025
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HU 4301 - Philosophy of Mind and Artificial Intelligence3 lecture hours 0 lab hours 3 credits Course Description The primary objective of this class is to engage in the philosophical study of the human mind by exploring the possibility of designing artificial intelligent systems. The project of artificial intelligence, or AI, can be seen as aiming in two directions. On the one hand, the goal is to use our philosophical understanding of the nature of mind to test the limits of implementing intelligence and mentality in a machine, an artifact. On the other hand, the goal is to test-or at least reflect upon-our understanding of the nature of mind by attempting to design one ourselves. Our own goal in this class will be to explore and assess attempts to meet both of these aims.
(prereq: none) Course Learning Outcomes Upon successful completion of this course, the student will be able to:
- Demonstrate knowledge of some of the history and philosophical foundations of the study of mind and AI
- Analyze and apply some of the key philosophical themes and concepts concerning the relationship between philosophy of mind and AI
- Anticipate and evaluate some of the applications, social implications, and future directions of the study of mind and AI
Prerequisites by Topic Course Topics
- Week 1: History of the study of mind and origins of AI
- Week 2: GOFAI (“good old-fashioned artificial intelligence”), computationalism, functionalism
- Week 3: Fodor’s Representational Theory of the Mind, Dennett’s Intentional Strategy
- Week 4: Some challenges to GOFAI, Part I: Consciousness, intentionality, and understanding
- Week 5: Some challenges to GOFAI, Part II: The Frame Problem, Dreyfus’s Critique
- Week 6: NFAI (“new-fangled artificial intelligence”), Part I: Connectionism
- Week 7: NFAI Part II: embedded and embodied AI
- Week 8: Beyond intelligence: emotions, free will, and moral agency
- Week 9: Social implications of AI: Human-AI interaction, AI and human labor, “Superintelligence”
- Week 10: Wild card week: Student-selected topics, recent AI news and case studies, or guest lectures
Coordinator Dr. Andrew McAninch
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