About

I am a philosopher working on the philosophy of science and epistemology. Currently, I am a postdoc at ETH Zurich where I am running my independent research project “MLS²: Machine Learning, Science, and Society” that is funded by an ETH Zurich Postdoctoral Fellowship. I am also an associate member of the Interchange Forum for Reflecting on Intelligent Systems (IRIS) at University of Stuttgart.

Previously, I was a research associate at University of Tübingen’s Cluster of Excellence “Machine Learning: New Perspectives for Science”. Within the research project “AITE – Artificial Intelligence, Trustworthiness and Explainability”, I worked on the philosophy of explainable artificial intelligence under the supervision of Wolfgang Spohn and Eric Raidl.
I hold a Ph. D. and an M. A. in Philosophy as well as an M. Sc. in Economics and Finance, all from University of Tübingen.

You can also find me on PhilPeople and on Google Scholar. Contact me at oliver [dot] buchholz [at] hest [dot] ethz [dot] ch.

Research

Philosophy of science, epistemology, machine learning, and the ways in which they interact.

News

• 03/19/2024 – My joint paper with Alessandro Blasimme, “Justifying Reasons in Medicine: Is There Room for ML?”, has been accepted for presentation at the 11th International Philosophy of Medicine Roundtable.
  
  
• 03/04/2024 – I have been approved as an associate member of IRIS, University of Stuttgart's Interchange Forum for Reflecting on Intelligent Systems.
  
  
• 02/12/2024 – I am happy to be part of the “ML, Explain Yourself!”-conference in Utrecht to give a talk on why a purely objectivist perspective seems inadequate for explicating the concept of explanation – in machine learning, but also in more general contexts.
  
  
• 10/08/2023 – My joint article with Thomas Grote, “Predicting and Explaining with Machine Learning Models: Social Science as a Touchstone”, has been accepted for publication at Studies in History and Philosophy of Science.
  
  
• 09/28/2023 – The website and program for the closing conference of our project “AITE – Artificial Intelligence, Trustworthiness and Explainability” are now online. Feel free to have a look here!
  
  
• 06/28/2023 – I have been awarded an ETH Zurich Postdoctoral Fellowship for my project “MLS²: Machine Learning, Science, and Society” that I will start working on in November.
  
  
• 06/22/2023 – My “Means-End Account of Explainable Artificial Intelligence” has been accepted for publication at Synthese.