Thomas Grote

Thomas Grote is a Research Fellow at the University of Tübingen's Ethics and Philosophy Lab within the Cluster of Excellence 'Machine Learning: New Perspectives for Science'. His research focuses on philosophical and ethical dimensions of artificial intelligence, particularly interpretability, fairness, and reliability in medical and social contexts. He co-supervises the Carl-Zeiss-Stiftung-funded project 'Certification and Foundations of Safe Machine Learning Systems in Healthcare' and co-organizes the 'Philosophy of Science Meets Machine Learning' conference series.

Research Focus

Grote's interdisciplinary work bridges philosophy of science and applied AI ethics. Key areas include:

• Methodological foundations of AI ethics and epistemology
• Clinical reliability and safety of ML systems
• Fairness metrics in sociotechnical healthcare systems
• Interpretability requirements for medical AI
• Computational psychiatry and evolving mental health frameworks

His recent publications demonstrate strong emphasis on healthcare applications, with critical analyses of reliability in foundation models, ethical paradigms for LLMs, and rethinking evaluation methodologies at the epistemology-ethics interface.