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Technical University of Munich

Initiative thesis topic: Human-AI Collaborative Task Solving

Type: Master

Date: Immediately

Supervisor: Nils Ness

Background

Generative Artificial Intelligence (GenAI) is transforming how people solve complex tasks. Modern Large Language Models (LLMs), combined with tools, retrieval systems, and agentic workflows, can support activities such as programming, writing, data analysis, and decision making. As these technologies become more capable, Human-AI collaboration is emerging as a key component of future knowledge work.

While AI can improve efficiency and performance, successful collaboration depends on more than technical capabilities alone. Performance is shaped by how cognitive work is shared between humans and AI, how users evaluate AI-generated information, and how responsibility is distributed throughout the task.

This research area combines Information Systems, Artificial Intelligence, and Human-Computer Interaction to design Human-AI systems that improve task performance while keeping humans meaningfully involved in the decision-making process.

Objective

Possible topics include, but are not limited to:

  • Human-AI collaboration strategies for problem solving
  • Cognitive load and performance during Human-AI collaboration
  • Trust, reliance, and calibration in AI-assisted decision making
  • Explainable AI and its influence on user behavior
  • Design and evaluation of Human-AI interaction concepts
  • Experimental studies using online platforms or laboratory environments
  • Eye tracking, EEG, or other physiological methods for investigating Human-AI collaboration

This is an umbrella topic covering multiple research directions. The specific thesis topic will be defined together based on your interests and current research projects.

Requirements

We are looking for motivated students with an interest in one or more of the following areas:

  • Human-AI interaction
  • Experimental research methods
  • Design research methods

Programming experience (e.g., Python or JavaScript) is beneficial for implementation-oriented theses but is not required for all topics.

Introductory Literature

  • Fügener, A., Walzner, D. D., & Gupta, A. (2025). Roles of Artificial Intelligence in Collaboration with Humans: Automation, Augmentation, and the Future of Work. Management Science, mnsc.2024.05684. https://doi.org/10.1287/mnsc.2024.05684
  • Hemmer, P., Schemmer, M., Kühl, N., Vössing, M., & Satzger, G. (2025). Complementarity in human-AI collaboration: Concept, sources, and evidence. European Journal of Information Systems, 34(6), 979–1002. https://doi.org/10.1080/0960085X.2025.2475962
  • Holldack, F., Banh, L., & Strobel, G. (2026). Agentic information systems. Electronic Markets, 36(1), 5. https://doi.org/10.1007/s12525-025-00861-0
  • Cognitive Load Theory. John Sweller, Paul Ayres, & Slava Kalyuga (2011). Cognitive Load Theory. Springer.
  • Fügener, A., Grahl, J., Gupta, A., Ketter, W., Ketter, W., & Ketter, W. (2019). Collaboration and Delegation between Humans and AI: An Experimental Investigation of the Future of Work. SSRN Electronic Journal.
  • Human-AI Collaboration. Shneiderman, B. (2022). Human-Centered AI. Oxford University Press.
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