(The lecturer of this course will be Dr. Matti Tedre)
This course looks at the philosophy of science from the viewpoint of computing disciplines. 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 understand and explain 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 successful science is actually done. As this course is aimed at people in computing disciplines, the examples will mostly come 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 lecturer of this course will be Dr. Matti Tedre)
We expect that by the end of this course all the course participants will:
- Be familiar with the basic positions in the philosophy of science.
- Be familiar with the history of the debates about the content and form of computer science
- Be able to connect the debates about what computer science is with the basic positions in the philosophy of science
- Be able to explain their own research topic in terms of the philosophy of science
- Be able to relate their own research with the paradigms of (computer) science; describe the intellectual foundations of their research; and explain some aspects of the applicability, limitations, and boundaries of their research results.
The course is organized around kick-off lectures, individual work, and a final workshop. The final 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 students.
Second-year doctoral students are advised to take this course, as its content may help them to prepare their PhD proposal.
Doctoral students in Computer Science have admission priority to this course.
