Books

• Explaining Artificial Intelligence. From Epistemological Foundations to Practical Consequences, under contract with De Gruyter.
  
  

Articles in peer-reviewed journals

• A Means-End Account of Explainable Artificial Intelligence, Synthese, 2023.
  [preprint] [journal]
  
  
• The Deep Neural Network Approach to the Reference Class Problem, Synthese, 2023.
  [preprint] [journal]
  
  
• Predicting and Explaining with Machine Learning Models: Social Science as a Touchstone (with Thomas Grote), Studies in History and Philosophy of Science, 2023.
  [journal]
  
  
• Analyzing the Relationship between Physicians' Experience and Surgery Duration (with Christopher Haager, Katja Schimmelpfeng, Jan Schoenfelder, and Jens Brunner), Operations Research for Health Care, 2023.
  [journal]
  
  
• A Falsificationist Account of Artificial Neural Networks (with Eric Raidl), The British Journal for the Philosophy of Science, 2022.
  [preprint] [journal]
  
  

Chapters in edited volumes

• AI Ethics Principles and Guidelines (with Marcello Ienca and Effy Vayena), forthcoming in: Ziosi, M., Floridi, L., and Taddeo, M. (eds.): The Blackwell Companion to Digital Ethics. Oxford: Wiley-Blackwell (invited).
  
  
• Digital Ethics (with Robert Ranisch and Effy Vayena), forthcoming in: Sugarman, J., and Sulmasy, D. P. (eds.): Methods in Medical Ethics. Scholarship, Practice and Policy in Bioethics. Washington, D.C.: Georgetown University Press (invited).
  
  
• Epistemology of AI and Politics (with Karoline Reinhardt), forthcoming in: Hähnel, M. and Müller, R. (eds.): The Blackwell Companion to Applied Philosophy of AI. Oxford: Wiley-Blackwell (invited).
  
  
• Machine Learning in Public Health and the Prediction-Intervention Gap (with Thomas Grote), forthcoming in: Durán, J. and Pozzi, G. (eds.): Philosophy of Science for Machine Learning: Core Issues and New Perspectives. Cham: Synthese Library (invited).
  [preprint]
  
  
• Maschinelles Lernen in der Wissenschaft, forthcoming in: Noller, J. and Reinhardt, K. (eds.): Handbuch Philosophie der Digitalität. Heidelberg: Metzler (invited).
  
  

Work in progress

• AI, Medicine and Reason: The Theoretical Challenges of Explainability (with Alessandro Blasimme), submitted.
  
  
• The Curve-Fitting Problem Revisited, submitted.
  
  

Theses

• Artificial Neural Networks and the Reference Class Problem, thesis for the degree M. A. in Philosophy, 2020.
  [thesis]
  
  
• Uncertainty and the Business Cycle, thesis for the degree M. Sc. in Economics and Finance, 2020.
  [thesis]