Philosophy of Artificial Intelligence

A 14-week asynchronous graduate course in which thought experiments become simulations, with lecture notes, interactive labs, Colab notebooks and weekly self-assessment

Each week turns a classic argument or thought experiment into something that can be run, changed and tested: a Turing machine, a Chinese Room rulebook, Braitenberg vehicles, a diagonalisation table, an integration measure or a hidden-state world. Progress is stored only in this browser.

This course is updated in line with current developments in the field. Last update: September 2026.

These materials were prepared for the graduate course 11118BLG003 Philosophy of Artificial Intelligence at Süleyman Demirel University. They are openly available: Anyone may use and adapt them in courses of related scope, with attribution, under the CC BY 4.0 licence for content and the MIT licence for code.

Weekly modules

1. 01What Is Artificial Intelligence? Definitions, Aims and MeasuresLectureInteractive labColab notebookPDF notesNot started
2. 02Can Machines Think? The Turing Test and Its CriticsLectureInteractive labColab notebookPDF notesNot started
3. 03Computation and Mind: Turing Machines, Symbol Systems and FunctionalismLectureInteractive labColab notebookPDF notesNot started
4. 04The Chinese Room and Its RepliesLectureInteractive labColab notebookPDF notesNot started
5. 05Symbol Grounding and MeaningLectureInteractive labColab notebookPDF notesNot started
6. 06Symbolic and Connectionist AI: Systematicity and CompositionalityLectureInteractive labColab notebookPDF notesNot started
7. 07Embodiment, Situatedness and the Extended MindLectureInteractive labColab notebookPDF notesNot started
8. 08The Frame Problem and Common SenseLectureInteractive labColab notebookPDF notesNot started
9. 09Limits of Machines: Gödelian Arguments and Dreyfus's CritiqueLectureInteractive labColab notebookPDF notesNot started
10. 10Consciousness: The Hard ProblemLectureInteractive labColab notebookPDF notesNot started
11. 11Machine Consciousness: Theories and Indicator PropertiesLectureInteractive labColab notebookPDF notesNot started
12. 12Understanding and World Models in Large Language ModelsLectureInteractive labColab notebookPDF notesNot started
13. 13Creativity and MachinesLectureInteractive labColab notebookPDF notesNot started
14. 14Intentionality, the Intentional Stance and Can Machines Think?LectureInteractive labColab notebookPDF notesNot started

Midterm and final capstones

1. MTMidterm Capstone: Machines, Tests and MeaningCapstone pageEnd of Week 7
2. FNFinal Capstone: Minds, Morals and MachinesCapstone pageEnd of Week 14