Workshop: Philosophical perspectives on artificial reasoning systems

Early LLMs were notorious for frequently generating outputs that, to users, appeared to contain basic reasoning errors. However, in recent years, researchers and AI developers have invested much effort in improving the common-sense and formal reasoning capacities of transformer-based models through reinforcement learning and similar techniques. This has led to a generation of 'large reasoning models’ that perform well on various benchmarks of reasoning problems. Still, questions remain about how we should interpret these capacities.
- Do large reasoning models really engage in reasoning, or merely in a statistical approximation of reasoning?
- What accounts of reasoning are available in the philosophical literature, and are these accounts applicable to LLMs?
- Do LLMs fare differently with respect different kinds of reasoning (e.g. common-sense reasoning, practical reasoning or counterfactual reasoning)?
- What are the risks of over-attributing reasoning capacities to LLMs?
This workshop brings together philosophers who work on these and related questions.
Attendance is open to anyone interested. We kindly ask attendees to register in advance by sending an email to Rebecca Sadowski (rebecca.sadowski@tu-dortmund.de) by October 23rd, 2026, stating:
- Your name
- Your institution / affiliation
Preliminary schedule
09:30-10:00
Opening
10:00-11:00
Gregor Betz (Karlsruhe Institute of Technology) and Joris Graff (TU Dortmund)
What Do We Mean When We Ask if LLMs Can Reason?
11:00-11:30
Break
11:30-12:30
Jaroslav Malik (University of Hradec Králové)
TBA
12:30-13:30
Lunch Break
13:30-14:30
Mirco Sambrotta (Slovak Academy of Sciences)
Can Statistical Predictions Alone Give Rise to Sapience?
14:30-14:45
Coffee Break
14:45-15:45
Cordelia Berz (LMU Munich)
Pearl, Not People? Counterfactual Reasoning in LLMs
15:45-16:00
Coffee Break
16:00-17:00
Leonard Dung and Thom-Felix Thormann (Ruhr-University Bochum)
Simulation and deceptive reasoning in LLMs
17:00-17:30
Closing






