Connectionists: Call for Participation: Workshop on Epistemological Issues of Machine Learning in Science

[HT, UDNN]

The Emmy Noether Group UDNN: Scientific Understanding and Deep Neural Networks (https://udnn.tu-dortmund.de/) invites participation in a two day workshop that marks the project’s kick-off.
Workshop on Epistemological Issues of Machine Learning in Science
27.–28.02.2024
Chaudoire Pavillon, TU Dortmund, Germany
Registration: udnn.fk14 at tu-dortmund.de<mailto:udnn.fk14 at tu-dortmund.de>
Website: https://udnn.tu-dortmund.de/index.php/activities/ws-epi-issues/
Description:
With impressive advances in Machine Learning (ML) and particularly Deep Learning, Artificial Intelligence is currently taking science by storm. This workshop brings together top scientists and philosophers working on fundamental issues connected to the use of Machine Learning in science. The workshop marks the launch of the DFG-funded Emmy Noether Group UDNN: Scientific Understanding and Deep Neural Networks, and is co-organized with the Lamarr Institute for Machine Learning and Artificial Intelligence and co-funded by the Department for Humanities and Theology at TU Dortmund University.
Topics include, but are not restricted to:

  *   The relation between prediction and discovery on the one hand, and explanation and understanding on the other, in fields of science that heavily rely on ML methods

  *   The key issues in identifying genuine discoveries and stable predictions by ML systems

  *   Core conceptions of “explanation” involved in the field of eXplainable AI (XAI), and their relation to philosophical theories of understanding and explanation

  *   Present limitations associated with ML’s predictive power and what may be needed to overcome them

  *   The connection between ML and traditional scientific means for prediction and discovery, such as theories, models, and experiments

  *   Our present understanding of ML itself and its limitations

Speakers

  *   Life Sciences
Jürgen Bajorath (University of Bonn)
Axel Mosig (Ruhr University Bochum)


  *   Machine Learning Theory
M. Klopotek (University of Stuttgart)
Marie-Jeanne Lesot (Sorbonne Université Paris)
David Watson (King’s College London)


  *   Philosophy
Kathleen A. Creel (Northeastern University Boston, MA)
Brigitte Falkenburg (TU Dortmund)
Konstantin Genin (University of Tübingen)
Lena Kästner (University of Bayreuth)
Henk de Regt (Radbout University Nijmegen)
Eva Schmidt (TU Dortmund)
Tom Sterkenburg (LMU Munich)


  *   Physics / Astronomy
Dominik Elsässer (TU Dortmund)
Michael Krämer (RWTH Aachen)
Mario Krenn (Max Planck Institute for the Science of Light)
Wolfgang Rhode (TU Dortmund)
Christian Zeitnitz (BU Wuppertal)

Registration is free but places are limited. To register, please send an E-mail to udnn.fk14 at tu-dortmund.de<mailto:udnn.fk14 at tu-dortmund.de> until January 15, 2024 including your name and institution. A small number of attendees will be able to join the conference dinner on the 27th on a dutch-treat basis. If you want to join the dinner, please indicate this in your registration.

Organizers
Annika Schuster, Frauke Stoll, and Florian J. Boge

UDNN – Scientific Understanding and Deep Neural Networks
TU Dortmund
Emil-Figge-Straße 50
44227 Dortmund
GERMANY


Wichtiger Hinweis: Die Information in dieser E-Mail ist vertraulich. Sie ist ausschließlich für den Adressaten bestimmt. Sollten Sie nicht der für diese E-Mail bestimmte Adressat sein, unterrichten Sie bitte den Absender und vernichten Sie diese Mail. Vielen Dank.
Unbeschadet der Korrespondenz per E-Mail, sind unsere Erklärungen ausschließlich final rechtsverbindlich, wenn sie in herkömmlicher Schriftform (mit eigenhändiger Unterschrift) oder durch Übermittlung eines solchen Schriftstücks per Telefax erfolgen.

Important note: The information included in this e-mail is confidential. It is solely intended for the recipient. If you are not the intended recipient of this e-mail please contact the sender and delete this message. Thank you. Without prejudice of e-mail correspondence, our statements are only legally binding when they are made in the conventional written form (with personal signature) or when such documents are sent by fax.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20231219/299cd048/attachment.html>