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This course is not a course in the philosophy of science in general, but in the philosophy of computer science, which is a specific subtopic of the philosophy of science. In this course we pose concrete, commonsensical, specific, and well-defined questions, such as "What kinds of methods do computer scientists use to investigate computing?" and "What is the subject matter of computer science?".
We are not going to speak much about science in general, but we are going to focus on computer science in particular. Our approach is a modern "naturalistic" approach to the philosophy of science in the sense that we are not going to speak much about how computer science should ideally be done, but we are going to focus on how computer science is actually done. We will analyze computer science in terms of philosophy of science and sociology of scientific knowledge. We are also going to talk about the subject matter of computer science - that is, what kinds of things do computer scientists study, how certain can we be about our results in computer science, and are our findings like "discoveries", "laws", or "products".
More specifically, the questions in this course include epistemological questions such as "What is knowledge in computer science and (how) is it different from beliefs and assumptions?", "How can one differentiate between knowledge and beliefs in computer science?", "Can computer scientists know some things with certainty?", "Are there things in computer science that cannot be proven (with certainty)?", "What is progress in computer science?", "Are new algorithms or programs progress?", "How does new knowledge about computing become a part of commonly held knowledge about computing?", and "Are there laws in computer science?". We also discuss methodological questions such as "How do computer scientists work and how should computer scientists work?" and "Do (should) computers scientists prove formulas like mathematicians do, build things like engineers do, or test hypotheses like natural scientists do?". And we also talk about ontological questions such as "What kinds of things (if any) in computer science are universal, or objective, or timeless?".
Note that we do not discuss the ethics of computing (we have another course for that), the philosophy of mind, or the philosophy of science in general. Most notably, we do not give undue emphasis on the philosophy of artificial intelligence.
For graduate (M.Sc) students this course offers an overview of the variety of things computer scientists work with, helps to understand different kinds of research in computer science, and offers insight into the debates about what computer science is and what computer scientists do. For postgraduate (PhD) students this course offers perspectives into one's own research topic/field, helps to locate one's work within the larger enterprise of computer science, lays a philosophical foundation of one's work, and sheds light on one's own research paradigm (why do we work as we do, how do our results relate to the broader intellectual landscape, what do our results mean, what is the product of our work and research?).
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