Books

• Explaining Artificial Intelligence. From Epistemological Foundations to Practical Consequences, De Gruyter, 2025.
  [book] [contents]
  
  

Articles in peer-reviewed journals

• The Curve-Fitting Problem Revisited, accepted for publication in the European Journal for Philosophy of Science.
  [preprint]
  
  
• Digital Bioethics: Exploring an Emerging Field (with Georg Starke, Wolf-Tilo Balke, Lasse Benzinger, Manuel Burghardt, Lukas J. Meier, Emilian Mihailov, Eva Seidlmayer, Robert Ranisch, Frank Ursin, Effy Vayena, and Sabine Salloch), Medicine, Healthcare and Philosophy, 2026.
  [journal]
  
  
• A Falsificationist Account of Artificial Neural Networks (with Eric Raidl), The British Journal for the Philosophy of Science, 2025.
  [preprint] [journal]
  
  
• Evaluating GPT-4's Ability to Generate Informed Consent Material for Genetic Testing (with Eirini Petrou, Kelly Ormond, Dominik Stammbach, Elliott Ash, and Effy Vayena), npj Artificial Intelligence, 2025.
  [journal]
  
  
• XAI: On Explainability and the Obligation to Explain (with Karoline Reinhardt), Digital Society, 2025.
  [journal]
  
  
• 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]
  
  

Chapters in edited volumes

• Prediction in the Social Sciences (with Sebastian Zezulka), forthcoming in: Hansson, S.-O. (ed.): Comprehensive Philosophy of Science. Amsterdam: Elsevier.
  
  
• Digital Ethics (with Robert Ranisch and Effy Vayena), in: Sugarman, J., and Sulmasy, D. P. (eds.): Methods in Medical Ethics. Scholarship, Practice and Policy in Bioethics. Washington, D.C.: Georgetown University Press, 2026.
  [link coming soon]
  
  
• AI Ethical Principles: The Debate (with Marcello Ienca and Effy Vayena), in: Floridi, L. and Taddeo, M. (eds.): A Companion to Digital Ethics. Oxford: Wiley-Blackwell, 2025.
  [chapter]
  
  
• Epistemology and Politics of AI (with Karoline Reinhardt), in: Hähnel, M. and Müller, R. (eds.): A Companion to Applied Philosophy of AI. Oxford: Wiley-Blackwell, 2025.
  [chapter]
  
  
• Machine Learning in Public Health and the Prediction-Intervention Gap (with Thomas Grote), in: Durán, J. and Pozzi, G. (eds.): Philosophy of Science for Machine Learning: Core Issues and New Perspectives. Cham: Synthese Library, 2025.
  [preprint] [chapter]
  
  
• Maschinelles Lernen in der Wissenschaft, in: Noller, J. and Reinhardt, K. (eds.): Handbuch Philosophie der Digitalität. Heidelberg: Metzler, 2025.
  [preprint] [chapter]
  
  

Commentaries and other short pieces

• Preventing Ethical Asymmetries: AI-Driven Decision-Aids for Prospective Participants in Clinical Research (with Lukas J. Meier, Robert Ranisch, and Sabine Salloch), The American Journal of Bioethics, 2026.
  [journal]
  
  

Work in progress

• A paper about the ethics of using AI in clinical research, accepted for publication.
  
  
• A paper about AI governance in science, under review.
  
  
• A paper about the epistemic foundations of human-LLM interactions, in preparation.
  
  

Theses

• Explaining Artificial Intelligence. From Epistemological Foundations to Practical Consequences, thesis for the degree PhD in Philosophy, 2023.
  [see ‘Books’ at the top of this page]
  
  
• Artificial Neural Networks and the Reference Class Problem, thesis for the degree MA in Philosophy, 2020.
  [thesis]
  
  
• Uncertainty and the Business Cycle, thesis for the degree MSc in Economics and Finance, 2020.
  [thesis]