Module CS3208-KP04

Duration

1 Semester

Turnus of offer

each winter semester

Credit points

4

Course of studies, specific fields and terms:

• Bachelor Interdisciplinary Courses for health sciences, optional subject, Interdisciplinary modules
• Master Interdisciplinary Courses, optional subject, Interdisciplinary modules
• Bachelor Interdisciplinary Courses, optional subject, Interdisciplinary modules

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:

• Prof. Dr.-Ing. Christian Herzog

Teacher:

• Institute for Electrical Engineering in Medicine
• Prof. Dr.-Ing. Christian Herzog
• Prof. Dr. Corinna Peifer
• Prof. Dr. Maria Henke
• Roman Spendler
• Prof. Dr. rer. nat. Floris Ernst
• Prof. Dr. rer. nat. habil. Ralf Möller
• Prof. Dr. André Calero Valdez
• Prof. Dr. med. Jürgen Westermann
• Prof. Dr. Doris Weßels
• Prof. Dr. Maximilian Schüler

Literature:

• : Various further literature from science and journalism

Language:

• German or English

Notes:

Last Updated:

02.10.2025