059021 VU Social Thinking in Computer Science (2024S)

The course follows an interdisciplinary approach: knowledge from computer science, psychology and sociology is put in relation to each other, and thus new perspectives, thoughts and views emerge. The individual models, theories and studies may be familiar to one or the other participant, but the added value for the participants comes from connecting knowledge and connecting with one another. Example filter bubble: Piaget's theory of cognitive development is established, the algorithms for ranking websites (as far as published) have already been discussed in detail in computer science. Eli Pariser has written an exciting book explaining how filter bubbles are created by algorithms that filter out irritating elements based on cognitive assimilation processes (i.e. irritation is avoided) and what effects this has on society - for example, reduced innovation due to the reduced occurrence of serendipity effects and the polarisation of society. Thus, this course leads from the technical to the social to the philosophical and from smaller to larger social systems by addressing the following questions:
- How can collaboration be organised to deal with complex computer science ventures?
- How can software tools (such as social media, AI,...) promote collaboration and what social effects can this have?
- How are human characteristics used to focus attention on software, e.g. social media, and what effects can this have?
- How does the use of ICT interact with social systems, using the example of using gpt3 (chat gpt) in science?
- How can data treasures be used for the common good?
- How does ICT affect social decision-making processes
- Beyond human kind?! Post- and transhumanism

The course relies heavily on group work and self-organised learning. The course leaders want to create a good frame for this and offer selected inputs in the form of established theories and empirical research.