Critical Thinking in Data Science and AI

Current developments in artificial intelligence (AI) and machine learning (ML), and also the increasing importance of dealing with big data in general, lead to important philosophical questions, especially re. epistemology. Typical examples are: To what extend are the results gained by means of AI and ML conclusive and transparent? When would underlying computational processes be considered “creative”? What is the relation between predictive success and scientific understanding?

A first overview of these and similar questions is offered in a blog post on "Philosophy of AI and the Role of Digital Design". In order to investigate these and other questions together with colleagues from the corresponding individual sciences, the Chair of Theoretical Philosophy collaborates in a number of research networks and centres (you can find more information on their websites):

These collaborations have so far resulted in a white paper on the role of artificial intelligence in drug development: "Rethinking Drug Design in the Artificial Intelligence Era" (Nature Reviews Drug Discovery). In addition, together with colleagues from architecture and web design, we developed a digital product of our own. The online whiteboard "KNOW" offers the possibility to combine different data formats, as they typically occur in teaching and project work (images, texts, comments ...), on a uniform interface and to develop them further together. Learn more.

: Prof. Dr. Dr. Norman Sieroka
Prof. Dr. Dr.

Norman Sieroka

Institution Philosophy (Phil BA)

Building/room: SFG 4190
Phone: +49 (0)421 218 67830


Universität Bremen
Institut für Philosophie, FB 9
Postfach 330 440
Enrique-Schmidt-Str. 7
28359 Bremen