"Machine Learning: Prediction Without Explanation?" is a 2-day workshop taking place from 17 to 18 February 2020 at the Karlsruhe Institute for Technology (KIT), Germany. It aims to bring together philosophers of science and scholars from various fields using Machine Learning techniques, to reflect on the changing face of science in the light of Machine Learning's constantly growing use. This workshop is organized by the project “The Impact of Computer Simulations and Machine Learning on the Epistemic Status of LHC Data” within the interdisciplinary, DFG/FWF-funded research unit “Epistemology of the LHC”.
Over the last decades, Machine Learning techniques have gained prominence in various areas of science. However, Machine Learning largely aim at predictions and does not seem to provide explanations for these, at least not in the same sense as predictions from theories or models do. Depending on the area of application, explanations may be desired or even necessary though. In this workshop, we want to address the complex of questions regarding scientific explanation that arise from this observation. These include, but are not restricted to:
- Will future science favor prediction above explanation?
- What methods are available to use Machine Learning results for explanations?
- What is the nature of these explanations?
- Does machine learning introduce a shift from the classical scientific explanation towards a statistical interpretation of explanation?