Project Trust in computer intensive methods
This project inquires which forms of trust are specific to computer intensive methods in science. Is it rational to trust these methods?
Project Using Algorithms to trust
This project looks into algorithms that try to make certain parts of trust explicit. What happens if it becomes explicit?
Blog
You can find scattered thoughts mostly on the philosophy of computational methods on the workshopping blog I run with Ramón Alvarado.
Scientific interests
- Philosophy of science/philosophy of technology
- Intertheoretical relations in physical theories (reduction, derivation, founding, modularity etc.)
- Computer simulatable physical theories (e.g. LatticeQCD)
- Computational reliabilism
- Constructing artifacts as pragmatic justification of scientific theories
- discrete vs continuous science
- Limits of statistical inference/learning
- Inductive assumptions in approxmative methods
- Machine Learning & the problem of induction
- Kolmogorov complexity as general framework for ML
- theoretical vs. practical limits (e.g. no free lunch theorems vs. FLOPs)
- Science and society
- Why trust science?
- Why trust society?
Work In Progress
Inductive assumptions in ML – often ignored, always required (Abstract)
Working for trust – when easy things become hard (Abstract)
The theory and practice of computational error (Abstract – of a talk with the same title given at IACAP 23)
Recent publications
- How I stopped worrying and learned to love opacity, Chapter for Philosophy of science for machine learning: Core issues and new perspectives (Juan Manuel Durán & Giorgia Pozzi (eds.)), Springer, forthcoming
- Hypothesis/Proposing Explanation in Simulation, Body of Knowledge for Modeling and Simulation, Springer 2023
- Branches of ethics, Body of Knowledge for Modeling and Simulation, Springer 2023
Publications that I especially like:
- Durán, J.M., Formanek, N. Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism. Minds & Machines 28, 645–666 (2018). https://doi.org/10.1007/s11023-018-9481-6
Recent talks
Slides available upon request.
- Bestätigung durch Konstruktion (HLRS-TUDa Kolloquium, Darmstadt, April 2nd, 24)
- Generalization and the problem of leakage – How not to make a fool out of yourself while using ML, (From Machine Learning to Deep Learning: a concise introduction, HLRS, March 28th, 24)
- LatticeQCD – between approximation and foundation (DPG Frühjahrstagung 24, Berlin, March 20th, 24)
- What is a numerical solution? (Talk in Claus Beisbart‘s philSci seminar, Bern, Nov 21st, 23)
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The continuum limit in Lattice QCD – what it means and why we need it (Discreteness and Precision in Physics, Paris, Nov 9th, 23)
- The epistemology of approximations in computer intensive science (POCFS, Hong Kong, Oct 11th, 23)
Teaching
- Philosophy of Computer Science (Summer term 2024, Uni Stuttgart)
- Computerethik (Winter term 2023, Uni Stuttgart)
- Limits of Computing (Summer term 2023, Uni Stuttgart)
Simulierte Welten
I am supervising two high-school students in the project Simulierte Welten. We are developing a topical model for the PhilosL mailinglist. This model automatically extract topics (i.e. metaphysics, philosophy of science, ethics) from the archives of the mailing list, allows to observe trends in topical distribution and evolution – and correlate topics with other interesting quantities. A more detailed description of the project can be found here (in German).