Connectionists: Lecture Series Philosophy of Science and Machine Learning: January 23, Nina Poth

[Schuster, Annika Noel]

We are delighted to invite you to our upcoming lecture series, Philosophy of Science and Machine Learning.

Lecture Series Overview: 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.

More information: https://udnn.tu-dortmund.de/index.php/activities/lecture-series-philosophy-of-science-and-machine-learning/

Upcoming Talk: We are excited to announce the next talk in the series:

Title: AI in Tension Between Cognitive Science and Society
Speaker: Nina Poth, Radboud University
Date & Time: January, 23, 2025, 4:15 PM CET
Location: TU Dortmund University

Talk Abstract:
In this talk, I examine the dual role of AI in both cognitive science and society. On one hand, significant ethical and theoretical concerns that call for caution in overstating the similarities between human-like intelligence and cutting-edge AI systems widely used today (such as AlexNet, GPT-4, etc.). On the other hand, cognitive scientists and philosophers view such deep neural networks as valuable tools for modelling and gaining insights into the human mind. These two perspectives stand in tension with one another that calls for a re-examination of the role of AI in cognitive science. While there are promising exploratory successes in specific domains such as perceptual categorisation, the contributions of deep neural networks to advancing our understanding of cognition are less revolutionary than often claimed and better put as a continuation of earlier revisions to computationalism, posing the worry that relative to the immense resources going in to building these models, the payoffs from theory lag significantly behind.

How to Attend:

  *   In-Person: Please send an e-mail to udnn.ht at tu-dortmund.de<mailto:udnn.ht at tu-dortmund.de>. If you would like to join us for dinner afterwards, please let us know so we can make a reservation.


  *   Online: Please register via the following form: https://forms.microsoft.com/r/W3whw0ac3B. We will send you a Zoom link before the talk.


We look forward to your participation and insightful discussions.

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" (https://udnn.tu-dortmund.de/)

Kind regards,

The UDNN team


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