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Graduate Degree
Artificial Intelligence Technology (PhD) ()
PHILOSOPHY OF ARTIFICIAL INTELLIGENCE
Course Information

Course Information

Course Information

Course Title	Code	Semester	L+U Hour	Credits	ECTS
PHILOSOPHY OF ARTIFICIAL INTELLIGENCE	803400815041		3 + 0	3.0	10.0

Prerequisites

None

Language of Instruction	English
Course Level	Graduate Degree
Course Type	Elective
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals	The aim of this course is to teach students the problems, concepts, and principles related to the philosophy of artificial intelligence
Course Content	Topics in Philosophical of Artificial Intelligence are gathered around four main issues. First, the historical and metaphysical roots of artificial intelligence. Second, the concepts “the very idea of artificial intelligence” that considers the possibility of building intelligent machines. Third, what can be the proper methods and tools in order to reach this possibility. Fourth, can artificial intelligence reach a singularity position that surpasses the cognitive capacity of human beings.The concepts and topics considered around these four issues will be introduced and discussed.
Learning Outcomes	1) Knowing the problems, concepts and principles related to the philosophy of artificial intelligence. 2) Analyzing different approaches to novel problems in artificial intelligence. 3) Analyzing different approaches to novel problems in artificial intelligence.

Weekly Topics (Content)

Week	Topics	Teaching and Learning Methods and Techniques	Study Materials
1. Week	A Very General Introduction to Philosophy of Artificial Intelligence	Lecture	Homework
2. Week	The Historical Roots of Artificial Intelligence	Lecture	Homework
3. Week	Artificial Intelligece Based On Certain Metaphysical Issues	Lecture	Homework
4. Week	The Birth of the Modern Idea of Artificial Intelligence	Lecture	Homework
5. Week	Erken Dönem Yapay Zeka Tartışmaları	Lecture	Homework
6. Week	Main Perspectives on the Philosophy of Artificial Intelligence	Lecture	Homework
7. Week	Main Principles of Strong Artificial Intelligence	Problem Solving; Discussion	Homework
8. Week	Opponents of the Strong Artificial Intelligence	Lecture	Homework
9. Week	Yapay Zeka ve İnsanın Biricikliği	Lecture	Homework
10. Week	Experts Systems and Weak Artificial Intelligence	Lecture	Homework
11. Week	Singularity	Lecture	Homework
12. Week	Discussions on Machine Learning	Lecture	Homework
13. Week	Artificial Intelligence in the Context of Language and Thought	Lecture	Homework
14. Week	Knowledge Representation and the Frame Problem	Lecture	Homework

Sources Used in This Course

Recommended Sources

Davis, M. (2018). The universal computer: The road from Leibniz to Turing. CRC Press.

Margaret A. Boden. (2008). Mind as machine: A history of cognitive science. Oxford University Press.

Relations with Education Attainment Program Course Competencies

Program Requirements	Contribution Level	DK1	DK2
PY1	5	5	5
PY2	5	5	5
PY5	5	5	5

*DK = Course's Contrubution.

	0	1	2	3	4	5
Level of contribution	None	Very Low	Low	Fair	High	Very High

.

ECTS credits and course workload

Event	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Total weeks*Hours per week)	14	3	42
Work Hour outside Classroom (Preparation, strengthening)	14	9	126
Homework	2	20	40
Presentation (Including Preparation Time)	1	20	20
Seminar	1	1	1
Midterm Exam	1	1	1
Time to prepare for Midterm Exam	1	20	20
Final Exam	1	1	1
Time to prepare for Final Exam	1	40	40
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course			30

Quick Access

Artificial Intelligence Technology (PhD)
Doktora (Eng)

Course Information

Course Information
Weekly Topics (Content)
Sources Used in This Course
Relations with Education Attainment Program Course Competencies
ECTS credits and course workload