Conceptual Foundations of Artificial Intelligence

Timetable

Module aim (aims)

• Deepening participants’ insights into conceptual foundations of AI. By AI we understand: the discipline; AI thesis; AI artifacts; and the issue of AI.
• Improving skills in working with scientific texts from various specialized disciplines.
• Improving skills in formulating and analyzing arguments related to the conceptual foundations of AI.

Pre-requisites in terms of knowledge, skills and social competences (where relevant)

Syllabus

1. What is AI? History of the AI idea.
2. How to make AI idea come true? AI paradigms.
3. What does it mean to be intelligence. Weak and strong AI.
4. The computational mind theory. How does it influence AI and cognitive-science research.
5. Is this agent ingelligent? How one may say? The Turing test.
6. The Turing test and more. Chat-bots, human-computer interaction and natural language.
7. The Turing test and more. How to design better tests for thinking machines?
8. Philosophical and ethical arguments against AI.
9. Arguments against AI – the frame problem.
10. Arguments against AI – limitation theorems.

Reading list

Obligatory

1. Robert M. Harnish, Minds, Brains, Computers. An Historical Introduction to the Foundations of Cognitive Science, Blackwell Publishers 2002.
2. Osherson, (Ed.), An Invitation to Cognitive Science - Thinking (p. 377-425), The MIT Press, London.
3. Lucas, J. R. (1961), Minds, Machines and Gödel, Philosophy, XXXVI, 112–127.
4. Moravec, H. (1999), Rise of the Robots. Scientific American, December 1999, 124–135.
5. Putnam, H. (1960). Minds and Machines, in: Sidney Hook, (ed.), Dimensions of Mind (p. 148–180), New York: New York University Press, 1960.
6. Searle, J. R. (1980) Minds, brains, and programs. Behavioral and Brain Sciences 3 (3): 417–457.
7. Turing, A.M. (1950). Computing machinery and intelligence. Mind, 59, 433-460.

 

Optional

1. Copeland, B. J. (Ed.). (2004). The essential Turing. Clarendon Press.