Upcoming

• Great, but Wait: Machine Learning in Science as a Challenge to AI Ethics, Colloquium in Practical Philosophy, Zurich, December 2025.
  
  

Previous

• Benign Overfitting and the Justification of Simplicity, Research Frontiers Workshop on Scientific Machine Learning, Stuttgart, October 2025.
  
  
• The Curve-Fitting Problem Revisited, Research Colloquium in Philosophy of Science, Bern, November 2024.
  
  
• AI and Dementia Prevention – Epistemology, Ethics, and Policy (with Mattia Andreoletti and Alessandro Blasimme), Future Memories Symposium, Rome, October 2024.
  
  
• Justifying Reasons in Medicine: Is There Room for Machine Learning? (with Alessandro Blasimme), 11th International Philosophy of Medicine Roundtable, virtual, May 2024.
  
  
• Against Objectivism about Explanation – in Machine Learning and Beyond, Conference “ML, Explain Yourself! Perspectives from Philosophy and Computer Science”, Utrecht, April 2024.
  
  
• Means-End Epistemology for Explainable Artificial Intelligence, Closing conference of the project “AI, Trustworthiness and Explainability”, Tübingen, October 2023.
  
  
• The Curve-Fitting Problem Revisited, Workshop on the Epistemology and Theory of Machine Learning, Munich, March 2023.
  
  
• A Means-End Account of Explainable Artificial Intelligence, Research Colloquium in Theoretical Philosophy, Frankfurt a. M., January 2023.
  
  
• A Falsificationist Account of Artificial Neural Networks (with Eric Raidl), Imre Lakatos Centenary Conference, London, November 2022.
  
  
• How to Use Explainable AI Responsibly (with Karoline Reinhardt), International Conference on Engaging Ethics and Epistemology in Science, Hannover, September 2022.
  
  
• The Curve-Fitting Problem Revisited, 11th International Congress of the German Society for Analytic Philosophy (GAP.11), Berlin, September 2022.
  
  
• The Curve-Fitting Problem Revisited, 4th International Conference of the German Society for Philosophy of Science (GWP.2022), Berlin, August 2022.
  
  
• Building Effective Guidelines for Machine Learning: Lessons from Means-End Epistemology, Conference on the Philosophy of Data Science: Data Science Governance, Frankfurt a. M., June 2022.
  
  
• XAI: On Explainability and the Obligation to Explain (with Karoline Reinhardt), Workshop on “Issues in XAI #4 – Explanatory AI: Between Ethics and Epistemology”, Delft, May 2022.
  
  
• The Curve-Fitting Problem Revisited, Conference on Formal Methods and Science in Philosophy IV, Dubrovnik, April 2022.
  
  
• A Means-End Account of Explainable Artificial Intelligence, Conference on Philosophy in Informatics VI, virtual, December 2021.
  
  
• A Means-End Account of Explainable Artificial Intelligence, Workshop “Philosophy of Science Meets Machine Learning”, Tübingen, November 2021.
  
  
• Building Effective Guidelines for XAI: Lessons from Philosophy, Workshop on Explainable AI in Finance at the 2nd ACM International Conference on AI in Finance, virtual, November 2021.
  
  
• The Deep Neural Network Approach to the Reference Class Problem, workshop “Philosophy of Science in Light of AI”, virtual, October 2021.
  
  
• A Means-End Account of Explainable Artificial Intelligence, 4th Conference on “Philosophy and Theory of Artificial Intelligence”, Gothenburg, September 2021.
  
  
• A Falsificationist Account of Artificial Neural Networks (with Eric Raidl), Congress of the Society for the Philosophy of Science, Mons, September 2021 (not held due to Covid-19 measures).
  
  
• A Falsificationist Account of Artificial Neural Networks, CEPE/IACAP joint conference, virtual, July 2021.
  
  
• A Falsificationist Account of Artificial Neural Networks, Philosophy of Science & Methodology Colloquium, Tübingen, June 2021. [recording]