Program

08:45-09:00 Arrival & registration

09.00-09:15 Welcome 

09:15-10:00 Daniel Herrmann (University of Groningen) Standards for belief representation in LLMs 

10:15-11:00 Sara Pernille Jensen (University of Oslo) Dissecting link uncertainty

11:15-12:00 Brent Mittelstadt (University of Oxford) Do large language models have a duty to tell the truth?

12:00-13:00 Lunch

13:00-13:45 Ana-Andreea Stoica (MPI Tübingen) Causal Inference from competing treatments 

14:00-14:45 Maximilian Noichl (Utrecht University) On Epistemic Virtues in Unsupervised Learning

14:45-15:30 Coffee break

15:30-16:15 Andreea Eșanu (New Europe College) Scrutinizing the foundations: could large language models be solipsistic

16:30-17:15 Molly Crockett (Princeton University) Monocultures of knowing in science & society 

19:00 Conference dinner at Freistil/Neckaw (covered)

09:00-09:15 Morning coffee  

09:15-10:00 Gabrielle Johnson (Claremont McKenna College) Precarious accurate predictions 

10:15-11:00 Frauke Stoll & Annika Schuster (TU Dortmund) Understanding without understanding

11:15-12:00 Donal Khosrowi (Leibniz University Hannover) Conceptual disruptions and the proper roles for ML in scientific discovery 

12:15-13:00 Lunch

13:00-13:45 Nico Formánek (University Stuttgart) What is overfitting? 

14:00-14:45 Hanseul Lee & Hyundeuk Cheon Transparency of what?

(Seoul National University) 

14:45-15:30 Coffee break

15:30-16:15 Hanna van Loo & Jan-Willem Romeijn Thick descriptions in data-driven psychiatry

(University of Groningen)

16:30-17:15 Stefan Buijsman (TU Delft) Evaluating the quality of explanations beyond fidelity

19:00 Dinner at El Pecado (self-pay) 

090-09:15 Morning coffee 

09:15-10:00 Julia Haas (DeepMind) Measuring for moral performance in foundation models

10:15-11:00 Benedikt Höltgen (University of Tübingen) Causal modeling without counterfactuals or generative distributions

11:15-12:00 Alexander Tolbert (Emory University) Causal agnosticism about race

12:00-13:00 Lunch

13:00-13:45 Bertille Picard (CREST-ENSAI) Does personalized allocation make our experimental designs more fair? 

14:00-14:45 Aydin Mohseni (Carnegie Mellon University) AI alignment as a principal-agent problem

14:45-15:30 Coffee break 

15:30-16:15 Dominik Janzing (Amazon Research) All causal DAGs are wrong but some are useful

16:15-16:45 Closing remarks and drinks

Tom Sterkenburg (LMU Munich) Values in machine learning: What follows from underdetermination? 

Please take into account that the program might change.