Duration:
1 Semester | Turnus of offer:
each winter semester | Credit points:
4 |
Course of studies, specific field and terms: - Bachelor Interdisciplinary Courses for health sciences (optional subject), interdisciplinary competence, Arbitrary semester
- Master Interdisciplinary Courses (optional subject), interdisciplinary competence, Arbitrary semester
- Bachelor Interdisciplinary Courses (optional subject), interdisciplinary competence, Arbitrary semester
|
Classes and lectures: - CS3208-V: Responsible Use of Generative AI (lecture, 2 SWS)
- CS3208-P: Responsible Use of Generative AI (not for medical students) (project work, 1 SWS)
| Workload: - 45 Hours private studies
- 45 Hours work on project
- 30 Hours in-classroom work
| |
Contents of teaching: | - Introduction - An overview of tools, possibilities and discourses on generative AI
- Fundamentals of Technology 1 - Basic Modes of Operation
- Fundamentals of Technology 2 - Adaptation to Social Norms
- Application basics - How to proceed when using generative AI?
- Psychological implications - effects on experience, motivation and skills in the workplace
- Use cases 1 - General productivity and scientific writing
- Use cases 2 - Research
- Use cases 3 - Training
- Use cases 4 - Medicine
- AI and security - The risks of AI in safety-critical applications
- Legal and Ethical Aspects - Intellectual Property, Privacy and Societal Challenges
- Sustainability - Environmental Costs
- The future - outlook on future possibilities and limitations
| |
Qualification-goals/Competencies: - Students will be able to explain the basic functioning and technology of generative AI in general content production.
- Students recognise the ethical and societal challenges of generative AI technologies and can formulate these concretely and precisely.
- Students are able to critically evaluate the impact of generative AI on their tasks.
- Students are able to use the potential of generative AI responsibly and reflectively in their studies and future work.
- The students know the basic legal framework around generative AI applications.
- Students are aware of the social and environmental implications of generative AI applications.
|
Grading through: - continuous, successful participation in course
- presentation
- project work
|
Responsible for this module: Teachers: |
Literature: - : Various further literature from science and journalism
|
Language: |
Notes:Admission requirements for taking the module: - None Admission requirements for participation in module examination(s): - None Module-Exam(s): CS3208-L1: Responsible Use of Generative AI, successful submission and presentation of a semester-long project, 100% of the (non existent) module grade |
Letzte Änderung: 14.10.2024 |
für die Ukraine