CFP: Philosophy of Science Meets Machine Learning
Submission deadline: February 15, 2020
June 17, 2020 - June 19, 2020
Cluster of Excellence: Machine Learning: New Perspectives for Science, Eberhard Karls University Tübingen
CfP: Philosophy of Science Meets Machine Learning
University of Tübingen, June 17-19, 2020
Convenors: Thomas Grote, Thilo Hagendorff, Eric Raidl
· Philipp Hennig (Tübingen)
· Anna Jobin (Zürich)
· Lena Kästner (Saarbrücken)
· Charlotte Stix (Eindhoven)
· Emily Sullivan (Eindhoven)
· Kate Vredenburg (Stanford/LSE)
· Gregory Wheeler (Frankfurt)
· Jon Williamson (Kent)
· Carlos Zednik (Magdeburg)
Machine learning does not only transform businesses and the social sphere, it also fundamentally transforms science and scientific practice. The workshop focuses on that latter issue. It aims to discuss whether and how exactly recent developments in the field of machine learning potentially transform the process of scientific inquiry. For this, it sets out to analyse the field of machine learning through the lenses of philosophy of science, epistemology, research ethics and cognate fields such as sociology of science. The workshop will bring together philosophers from different backgrounds (from formal epistemology to the study of the social dimensions of science) and machine learning researchers. The workshop`s central topics are:
(i) A critical reflection on key-concepts, such as ‘learning’, ‘inference’, ‘explanation’ or ‘understanding’.
(ii) The implications of machine learning for the special sciences, e.g. cognitive science, social science or medicine.
(iii) The ethics of machine learning-driven science, e.g. the moral responsibilities of researchers.
(iv) Social aspects of machine learning-driven science, e.g. the impact of funding structures on research.
The workshop is organised by the ‘Ethics and Philosophy Lab’ of the Cluster of Excellence ‘Machine Learning: New Perspectives for Science’ at the University of Tübingen.
The call for abstracts is opened. We particularly welcome young researchers who have recently started to work on Machine Learning from a philosophical perspective. Please submit an anonymised extended abstract (750 words not including references) until 15 February, 10 p.m. to: https://easychair.org/conferences/?conf=mlphil1
For young researchers, who do not have internal funding, we are able to subsidize the costs for travel and lodging (the details need to be discussed once the accepted papers have been selected).
For further questions, please send an email to: firstname.lastname@example.org