[Deadline extended] Causality in the Age of AI Scaling Workshop at AISTATS 2026
Bryon Aragam
Don't miss your chance to submit your work to the Causality in the Age of AI Scaling Workshop at AISTATS 2026! The deadline has been extended to Tuesday March 3 (AoE). We invite submissions broadly related to causality, scaling, and its interface.
Important info:
AISTATS 2026 Workshop on Causality in the Age of AI Scaling
Website: https://causcale.github.io/
Extended deadline: Tuesday March 3 (AoE)
Workshop information
We are excited to announce our AISTATS workshop “Causality in the Age of AI Scaling”, taking place on May 5, 2026 in beautiful Tangier, Morocco.
This workshop aims to understand and explore the potential synergy between scaling predictive methods and formal causal modeling in order to build the next generation of AI.
Reasoning about interventions, the core of causality, is fundamental to solving many of modern AI’s most pressing challenges, yet recent AI breakthroughs have been overwhelmingly driven by scaling models without explicit causal modeling. This success raises a critical question: Can causal abilities emerge from scale alone, and if not, what can explicit causal modeling bring that scale cannot?
Submissions
We invite submissions of short papers presenting recent work on causality, scaling, and its interface. Submissions will be handled via OpenReview. Submissions under review or accepted within the past year at other venues are allowed.
Potential topics include, but are not limited to:
- Emergence of causal abilities in foundation models
- OOD generalization and robustness of large models
- Scaling causal generative modeling and representation learning
- Causal, counterfactual, and logical reasoning in large models
- Design of interactive causal world models
- Trustworthy and interpretable AI
- Causal discovery and abstraction
- Evaluation and benchmarking
Website: https://causcale.github.io/
Submission deadline: March 3, 2026
Workshop date: May 5, 2026
Organizers:
David Inouye (Purdue University)
Bryon Aragam (University of Chicago)
Murat Kocaoglu (Johns Hopkins University)