Introductory description

The purpose of this module is to provide a non-technical introduction to computer science and philosophical issues about computation and artificial intelligence. Among the questions we will address are the following: What is computation? What is an algorithm? What is computational complexity? Are all problems solvable by algorithms? What does it mean for a physical system to compute? What is the role of computation in mathematics and the sciences? What is the role of computation in society? What is meant by "intelligence" and "artificial intelligence"? What prospects and challenges are posed by specific developments in artificial intelligence (e.g. machine learning, large language models)?

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

• Week 1: Introduction: Computer science and artificial intelligence as disciplines
• Week 2: Algorithms, programs, correctness
• Week 3: Complexity, intractability, and non-computability
• Week 4: Machines, computation, and physics
• Week 5: Computation and mathematics
• Week 7: Computation and society
• Week 8: Artificial intelligence I: History and the logical paradigm
• Week 9: Artificial intelligence II: Machine learning and the statistical paradigm
• Week 10: Artificial intelligence III: safety, ethics, existential risks, the future

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate knowledge of central topics in the philosophy of computation and artificial intelligence. (Subject knowledge and understanding.)
• Understand the significance that questions in philosophy of computation and artificial intelligence have to wider issues in philosophy, mathematics, the sciences. (Cognitive skills)
• Articulate their own view of the relative merits of different theories and engage critically with the arguments put forward in support of them (key skills).
• Show an understanding of methodological issues in the philosophy of mathematics, and of questions of demarcation between philosophy and mathematics (subject-specific skills)

Indicative reading list

Readings will be drawn from a variety of sources including the following:

• Harel, D. Algorithmics: the spirit of computing. Addison-Wesley, Reading, Massachusetts, 2006.
• Moore, C., and Mertens, S. The Nature of Computation. Oxford University Press, 2011.
• Shagrir, O. The nature of physical computation. Oxford University Press, 2022.
• Russell, S. J., and Norvig, P. Artificial intelligence: a modern approach. Pearson, 2021.
• Hofstadter, D. R., and Dennett, D. C. The mind’s I: Fantasies and reflections on self and soul. Bantam Books, 1981.
• Bostrom, N. Superintelligence: Paths, dangers, strategies. Oxford University Press, 2014.
• The Stanford Encyclopedia of Philosophy

Subject specific skills

Show an understanding of methodological issues in the philosophy of computation and artificial intelligence, and of questions of demarcation between philosophy and computer science.

Transferable skills

Understanding of how development in computer science and artificial intelligence bear on traditional topics in philosophy (e.g. the nature of the mind and consciousness), other academic disciplines (e.g. mathematics, the physical and social sciences) and contemporary debates outside of academia (e.g. in regard to privacy, the use of algorithms and machine learning in public policy, the workplace, surveillance, ethics, safety, and existential risk in regard to artificial intelligence).