The lecturer of this course will be Prof. Matti Tedre.
Course Description:
This course looks at the philosophy of science from the viewpoint of computing. In this course we pose concrete, commonsensical, specific, and well-defined questions about the nature of science, how science should be done and how it is done, and how can one best explain and understand the nature of science. 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 science should ideally be done, but we are going to focus on how it is actually done. As this course is aimed at people in computing disciplines, the examples will mostly be from the field of computing. We will analyze science in terms of philosophy of science and sociology of scientific knowledge. We are also going to talk about the subject matter of science in the context of computing’s disciplinary debates - 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 scientific knowledge and (how) is it different from beliefs and assumptions?", "How can one differentiate between knowledge and beliefs in science?", "Can (computer) scientists know some things with certainty?", "Are there things in 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 specific to computing, 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 this course does not discuss the ethics of science, the philosophy of mind, artificial intelligence, or specialized topics in the philosophy of science.
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 science as well as 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?). This course also 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.
The course is organized around individual on-line work, face-to-face lectures, workshop presentation of students' individual work, and final essay. The workshop is mandatory, as it includes presentation of one’s work to the audience as well as critical opposition of other participants’ reports.
This is a Fundamental PhD Course of the Faculty of Informatics for doctoral and master students.
Doctoral students in Computer Science have admission priority to this course.
Schedule: The course will start on Oct 28, 2019, with learning and reading assignments.
The grading will be based on the performance in the individual on-line work, contribution to discussions in the face-to-face lectures, workshop presentation of the students' individual work and the quality of the final essay.
Textbook: Tedre, Matti (2014) The Science of Computing: Shaping a Discipline. Taylor & Francis / CRC Press.
Supplementary reading: Denning, Peter J. & Tedre, M. (2019) Computational Thinking. The MIT Press.
Other literature (journal articles) is presented over the course.
