Universität Wien
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059021 VU Social Thinking in Computer Science (2023S)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 17.03. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 31.03. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 21.04. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 28.04. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 12.05. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 19.05. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 02.06. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG
  • Friday 09.06. 13:15 - 16:30 PC-Unterrichtsraum 4, Währinger Straße 29 1.OG

Information

Aims, contents and method of the course

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.

Assessment and permitted materials

Regular participation, preparation and reflection of discussions on one of the main focuses of the course, team project

Minimum requirements and assessment criteria

Both the work process in the course and the products of the team and individual work, to an extent of around 50% each, are used for assessment.

Examination topics

Selected literature and the contents taught in the course, especially on the following topics:
1. cooperation in technology development - diversity and agile methods
2. the "open" movement - open source, open data, hacking
3. Basic understanding of the technology behind generative artifical intelligence and the implications for science and research

Reading list

Literature:
https://docs.google.com/document/d/1D01YlG-vNEgUc3y6A-ypXfuG8Hytvgk-0MVtYHiFffg/edit?usp=sharing

Association in the course directory

Module: SDI

Last modified: Mo 05.06.2023 07:47