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White, H. and Chalak, K. (2009) Settable Systems: An Extension of Pearl’s Causal Model with Optimization, Equilibrium, and Learning. Journal of Machine Learning Research, 10, 1759-1799.

has been cited by the following article:

• TITLE: Causal Inference, Fast and Slow

  AUTHORS: Sergio Da Silva

  KEYWORDS: Causal Inference, Causal Diagrams, Causal Networks, Statistical Inference, Data-Driven Decision Making, Dual-Processing Theory of the Mind

  JOURNAL NAME: Open Access Library Journal, Vol.11 No.7, July 30, 2024

  ABSTRACT: This paper explores causal inference through cognitive psychology, focusing on the dual-processing theory of the mind, which includes fast (System 1) and slow (System 2) thinking. It explains that our fast thinking, geared towards identifying causes, helps us survive but can also lead to incorrect causal inferences. The paper underscores the need for slow, deliberate thinking in accurately determining cause-and-effect, a challenging but essential approach. It outlines established methods for developing precise causal inference frameworks and highlights the need for a balanced approach in research, utilizing both systems for creating effective causal diagrams. It proposes using the “thinking, fast and slow” concept to combine System 1’s intuitive reasoning with System 2’s thorough causal analysis, improving causal inference in everyday research.