Causal Emergence: When Distortions In A Map Obscure The Territory

APA

(2022). Causal Emergence: When Distortions In A Map Obscure The Territory. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/causal-emergence-when-distortions-map-obscure-territory

MLA

Causal Emergence: When Distortions In A Map Obscure The Territory. The Simons Institute for the Theory of Computing, Feb. 14, 2022, https://simons.berkeley.edu/talks/causal-emergence-when-distortions-map-obscure-territory

BibTex

          @misc{ scivideos_19675,
            doi = {},
            url = {https://simons.berkeley.edu/talks/causal-emergence-when-distortions-map-obscure-territory},
            author = {},
            keywords = {},
            language = {en},
            title = {Causal Emergence: When Distortions In A Map Obscure The Territory},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {feb},
            note = {19675 see, \url{https://scivideos.org/Simons-Institute/19675}}
          }
          
Frederick Eberhardt (Caltech)
Source Repository Simons Institute

Abstract

We provide a critical assessment of the account of causal emergence presented in Hoel (2017). The account integrates causal and information theoretic concepts to explain under what circumstances there can be causal descriptions of a system at multiple scales of analysis. We show that the causal macro variables implied by this account result in interventions with significant ambiguity, and that the operations of marginalization and abstraction do not commute. Both of these are desiderata that, we argue, any account of multi-scale causal analysis should be sensitive to. The problems we highlight in Hoel's definition of causal emergence derive from the use of various averaging steps and the introduction of a maximum entropy distribution that is extraneous to the system under investigation. (This is joint work with Lin Lin Lee.)