[spsp-members] Lecture Series Philosophy of Science and Machine Learning

[Anni S.]

 In an age where artificial intelligence (AI) is transforming science, it
becomes increasingly important to reflect critically on the foundations,
methodologies, and implications of these advancements. This lecture series
will investigate fundamental issues in AI from the vantage point of
philosophy of science, which includes topics such as the transparency and
interpretability of AI within scientific research, as well as the impact of
AI on scientific understanding and explanation.

The talks will be held on Thursdays at 4:15 PM.

Speakers:

17.10.24 André Curtis-Trudel – "On finding what you’re (not) looking for:
prospects and challenges for AI-driven discovery"

28.11.24 Tim Räz – "The Concept of Memorization in Machine Learning”

12.12.24 Stefan Buijsman – TBA

23.01.25 Nina Poth – "Common Sense and the Limits of AI”

This lecture series is a special edition of the AI Colloquium at TU
Dortmund University, co-organized by the Lamarr Institute for Machine
Learning and Artificial Intelligence, the Research Center Trustworthy Data
Science and Security (RC Trust), and the Center for Data Science &
Simulation at TU Dortmund University (DoDas). The Lecture Series is
organized by the Emmy Noether Group "UDNN: Scientific Understanding and
Deep Neural Networks”.

Participation is free, but places are limited. If you are interested in
participating online, please register via the following form:
https://forms.microsoft.com/r/W3whw0ac3B. If you would like to attend in
person, please send an e-mail to udnn.ht at tu-dortmund.de.

We look forward to your participation and insightful discussions.

Kind regards,

The UDNN team (https://udnn.tu-dortmund.de/)
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