Seeing Versus Doing: Two Modes of Accessing Causal Knowledge

The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, whose parameters were learned in a purely observational learning phase, depending on whether learners believe that an event within the model has been merely observed ('seeing') or was actively manipulated ('doing'). The predictions reflect sensitivity both to the structure of the causal models and to the size of their parameters. This competency is remarkable because the predictions for potential interventions were very different from the patterns that had actually been observed. Whereas associative and probabilistic theories fail, recent developments of causal Bayes net theories provide tools for modeling this competency. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

Accession Number: 2005-02160-003. PMID: 15755240 Other Journal Title: Journal of Experimental Psychology: Human Learning and Memory. Partial author list: First Author & Affiliation: Waldmann, Michael R.; Department of Psychology, University of Göttingen, Göttingen, Germany. Release Date: 20060710. Publication Type: Journal (0100), Peer Reviewed Journal (0110). Format Covered: Electronic. Document Type: Journal Article. Language: English. Major Descriptor: Causal Analysis; Knowledge Level; Observational Learning; Reasoning. Classification: Cognitive Processes (2340). Population: Human (10). Location: Germany. Age Group: Adulthood (18 yrs & older) (300). Methodology: Empirical Study; Quantitative Study. References Available: Y. Page Count: 12. Issue Publication Date: Mar, 2005. Publication History: Accepted Date: Sep 2, 2004; Revised Date: Sep 1, 2004; First Submitted Date: Apr 15, 2004. Copyright Statement: American Psychological Association. 2005.