Human AI Interaction (WP)*

Master

The participants:
• are able to explain the basic principles of human–AI interaction and can apply these to modern AI systems such as LLMs, chatbots, agents, and decision-making systems
• are able to analyse user needs, tasks, and usage contexts when interacting with AI
• are able to develop interaction models and UX patterns for AI systems
• are able to analyse the distribution of roles between humans and machines and can design various application scenarios

None

• Fundamentals of Human–AI Interaction
• Human cognition, mental models, decision-making behavior
• HCI principles for AI systems
• UX Design for AI
• Interaction patterns (conversational UI, agents, multimodal interfaces)
• Prompt design, system messages, feedback loops
• Trust and user acceptance
• Human-in-the-Loop & Human-on-the-Loop
• Alignment of human–machine roles
• Task distribution, limits of automation
• Error prevention & recovery design
• Empathetic & Social Aspects of AI Interaction
• Social responses, trust
• Persuasive and adaptive systems
• Methods & Tools
• Usability testing for AI systems
• Prototyping tools
• Evaluation methods (task success, trust metrics, cognitive load)

• Norman, D. (2013): The Design of Everyday Things
• Rogers, Y., Sharp, H. (2023): Interaction Design: Beyond Human–Computer Interaction
• Sheiderman, B. (2013): Designing the User Interface
• Kempka, D., Nudelman, G. (2025): UX for AI
• Shneideman, B. (2022): Human-Centered AI
• Rahwan, I. (2018): Society-in-the-loop: programming the algorithmic social contract

Seminar paper

English

4

Lecture, group work, presentation and discussion of tasks

3