|Event date||May 18, 2023 - May 20, 2023|
|Submission deadline||February 01, 2023|
|Host(s)||University College London|
Heuristics and Causality in the Sciences (HaCitS)
University College London, London, UK
18-20 May 2023
This is the fourteenth conference in the Causality in the Sciences series of conferences. Causality plays a central role in the sciences. Causal inference, explanation and reasoning are major concerns in fields as diverse as computer science, psychology, astrophysics, biochemistry, biomedical or social sciences.
Following Herbert Simon’s work, ideas of heuristics have also been pervasive in fields as diverse as computer science, psychology, and game theory and are recently of interest in questions of evidence in philosophy of biology and biomedical sciences. Heuristics have been understood in many ways, but they are united by offering problem solving or discovery methods when traditionally ‘optimal’ search is impossible or otherwise undesirable.
These ideas have influenced thinking in many disciplines, and this conference aims to bring together researchers from multiple disciplines, working on diverse questions of heuristics and causality. We offer some suggested topics of interest but encourage submission of abstracts on all related topics:
– What are heuristics, and what does it mean to search for causes in some less than optimal way?
– Should we seek one best view of heuristics, or is there potentially a toolbox of heuristic formalisms that may apply to different areas?
– How should we think about heuristics for non-formal evidence of and reasoning about causality?
– Are there heuristics that are particularly fruitful for model-building (perhaps for a specific domain)?
– How does – or should – heuristic search change how we use the resulting evidence or models?
– Computational methods for causal inference and the tradeoff between provably correct methods (with strong assumptions) and heuristic methods (that work in reality but have no guarantees)
– Judgment and decision-making heuristics and how causes fit in
Phyllis Illari (Science and Technology Studies, UCL)
Samantha Kleinberg (Computer Science, Stevens Institute of Technology)
and David Lagnado (Psychology, UCL).
Tobias Gerstenberg, Stanford
Dan Goldstein, Microsoft Research
Sam Johnson, U of Waterloo
Anne Ruth Mackor, Groningen
Lauren Ross, UC Irvine
– 1 February 2023: deadline for submission of abstracts (300 words) vis Microsoft CMT https://cmt3.research.