With the intimate entanglement of digital technology with humans and their social way of being, informatics has changed. While many problems still are hard and solve-able like when informatics was mostly mathematics, others are wicked and ill-defined. People and technologies are now part of an interwoven socio-material web in which humans are not the only actors anymore. This pervasive complexity rises challenges for computer scientists and technologists that go well beyond of what could be addressed by a traditional understanding of computer science, i.e. engineering the most efficient computational tools. It requires us to rethink what the core competencies of computer scientists of the future need to be.
New skills stemming from the social sciences or philosophy need to complement engineering skills to create digital technologies within lived experiences. With it comes a major shift in responsibility. Technologists, whether working in dominating corporations, small start-ups or within academia, can no longer pretend they only solve tech problems, but are required to engage in a moral discourse as most of their products or results are essentially social interventions.
How can we facilitate such a shift in the thinking as well as in the culture, especially in teaching informatics at the university level? In an attempt to answer that question, we created an entry-level course: »Ways of Thinking in Informatics«.
Its core premise is to enable students to think about problems in computer science in different ways and from different perspectives. The aim is to plant the seed of critical reflection and equip students with the intellectual tools to see everything they hear subsequently as part of something bigger, as part of something that could be thought of in different ways – hence the title, »Ways of Thinking in Informatics«.
One of the initial ideas was to make a course that can be understood as an applied philosophy of science lecture, suitable for first semester students. In order to understand the enormous changes that the scientific revolution brought about, we start with a brief introduction to alchemy as an example for pre-scientific thinking. We show that one of the key differences between alchemy and science was openness, or more specifically the lack thereof. Alchemy was based on secrets, hermetism and isolation. One of the key insights enabling the scientific revolution was the realisation that open exchange and critical discourse should replace the secrecy and isolation of alchemy, and that striving for knowledge is more important than striving for money. We of course point out the interesting parallel that especially in informatics, academic patenting and privately funded research has recently increased the need for secrecy, with unknown side effects, e.g. in terms of accountability