Scorzato’s Reliability and Interpretability in Science and Deep Learning is one of the few epistemology of ML papers which has a strong grasp of recent technical results in ML. It succeeds in connecting these results to a wider philosophical discussion without inventing artificial philosophical problems in ML.Scorzato starts by discussing recent technical approaches to error estimation in ML. The epistemological problem… Continue reading Finally, a paper on the philosophy of error analysis in ML
Category: ML-epistemology
LLMs and meaning (again)
Jumbly Grindrod has a recent paper arguing that LLMs produce meaningful output. He makes an argument fielding teleosemantic theories very similar to the argument advanced by Lyre. He differs from Lyre by thinking that the success of LLMs is also evidence for the distributional hypothesis, something that is not discussed by Lyre at all. I… Continue reading LLMs and meaning (again)
Does clustering identify natural kinds?
This is just a quick comment on a recent debate in Philosophy & Technology between David Watson and Tom Sterkenburg. They discuss if clustering methods, nowadays classed as a type of machine learning, can find natural kinds. The point of contention is an epistemic claim by Watson: Some clustering algorithms can identify some natural kinds.… Continue reading Does clustering identify natural kinds?
The illusion of generalization
Contrary to optimistic claims in ML literature, I often cannot help but think that deep neural nets are indeed overfit and do not generalize well. But of course that claim hinges on what one means by generalizing well. About this there has been considerable confusion in the more practical engineering oriented ML literature, which at… Continue reading The illusion of generalization
ML epistemology workshop – Day 1
I recently attended Tom’s closing workshop on his Philosophy of statistical learning theory project. It was a great workshop and I learned a great deal from the talks. I provide a streamlined version of notes I took, for all those who were interested but couldn’t attend. The abstracts of the talks can be found here: https://www.mcmp.philosophie.uni-muenchen.de/events/workshops/container/ml_2023/index.html#schuster.… Continue reading ML epistemology workshop – Day 1
Two positions in epistemology of ML
My friend Florian Boge is looking for a PhD and a Postdoc for his upcoming project Scientific Understanding and Deep Neural Networks at TU Dortmund. This project will try to get a better grasp at concepts of explanation and understanding in XAI using the philosophy of science toolbox. It was also featured in The List… Continue reading Two positions in epistemology of ML
The strangest error
If the problem of induction is unsolvable then we won’t have a theory of strange errors. If the new problem of induction is unsolvable then we won’t have a theory of artifacts in ML. A problem in ML which has not received too much attention in philosophical circles so far is the problem of strange… Continue reading The strangest error
List of current ML epistemology projects
There seems to be a flurry of funding for ML epistemology projects with lots of them starting in 2023. This list my attempt to get on overview what is going on in the field. I try to include only projects with a very specific ML epistemology focus (or at least epistemology has to be in… Continue reading List of current ML epistemology projects