Stochastic Systems – Dirk Baecker (Friedrichshafen)

Abstract:

Digital complexity eludes human understanding not only because it is based on the synchronization of incommensurable systems, but also because each of these systems operates stochastically. We owe this insight to the “synthetic intelligence” (Brian Cantwell Smith) of machine learning models. An initially random variation of model assumptions enables the discovery and description of chance-dependent structures of an object or field ‘out there’. Stochastic systems “tame” (Ian Hacking) chance with the help of chance. This may apply not only to artificial systems, but also to neural, mental, and social systems. And perhaps their stochasticity is the condition of possibility for their synchronization, which can only ever be temporary. The lecture outlines a basic understanding of technology, society, consciousness, and the brain in order to plausibly demonstrate that we are dealing with stochastic systems here. It discusses three concepts that can be used to describe the synchronization of these systems. The concept of information comes from computer science and formulates a relational understanding of information. The concept of feedback comes from cybernetics and brings the observer into play. And the concept of chance comes from stochastics and establishes a medial as well as formal understanding of reality. Digital complexity arises from the unavailability of the difference between the systems involved.

This event is part of our winter term 2025/26 Lecture Series Digital Complexity: Beyond Human Understanding.

If you would like to attend, please register with events@khk.rwth-aachen.de.