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| Detailed information |
| Original study plan |
Bachelor's programme Computer Science 2022W |
| Objectives |
Students
- are aware of social, ethical and gender relevant implications of new technologies
- know crucial international policies and regulatory measures
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| Subject |
Ethics
- Introduction to ethical issues of technology research and development focusing on AI & robotics using current practical examples
- Presentation and discussion of ethics-related codes of conduct for computer scientists (e.g. IEEE)
- Content of current ethics guidelines and regulatory approaches (e.g. "Ethics Guidelines for Trustworthy AI "and related Policy Recommendations of the European Commission)
- Reproduction of socialized stereotypes through data-driven AI, discussion of practical examples and possible counter-strategies
Gender
- Introduction to gender and diversity from the point of view of neuroscience and neurodidactics
- Presentation and discussion of aspects and questions on gender and diversity in technology and computer science (e.g. gender gap with respect to interest and learning outcomes, challenges for women in technical / IT occupations, different approaches of problems solving, different preferences, etc.)
- Gender stereotypes - a grain of truth?
- Self-concept as a key influencing factor on the gender gap in the area of computer science/technology
- Gender neutrality - how should this work? Experiences from the project "Gender meets Informatics"- design of gender-neutral and gender-sensitive computer science lessons and materials for pupils and students
- Addictive factors of online games (how do online games change the social behavior of children and adolescents, influence on cognitive development ...)
Ethics, gender and diversity in practice
- Discussion of experiences and/or interests of students in the context of LVA topics
- Implementation of smaller (empirical) projects on LVA topics in schools, universities and/or companies
- Discussion of measures and strategies for the (future) handling of questions and problems around ethics, gender and diversity in computer science/technology
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| Criteria for evaluation |
Short presentation, written paper, participation (examination), team work
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| Methods |
- Combination of presentation parts and interactive elements
- Linkage of LVA-relevant theories, scientific-empirical literature and current practical examples
- Project-based learning
- Flipped classroom
- Team work
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| Language |
German |
| Study material |
- Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183-186.
- HLEG AI (2019). Ethics Guidelines for Trustworthy AI. Online verfügbar via https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines
- Gurian, M. (2010). Boys and girls learn differently! A guide for teachers and parents: Revised 10th anniversary edition. John Wiley & Sons.
- More references in the course
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| Changing subject? |
No |
| Corresponding lecture |
(*)INBPGKVETHI: KV Ethik in Naturwissenschaft und Technik (3 ECTS)
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