ISSN:
1572-8641
Keywords:
cause
;
causation
;
directed graphs
;
explanation
;
judgment
;
under certainty
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Philosophy
Notes:
Abstract I argue that psychologists interested in human causal judgment should understand and adopt a representation of causal mechanisms by directed graphs that encode conditional independence (screening off) relations. I illustrate the benefits of that representation, now widely used in computer science and increasingly in statistics, by (i) showing that a dispute in psychology between ‘mechanist’ and ‘associationist’ psychological theories of causation rests on a false and confused dichotomy; (ii) showing that a recent, much-cited experiment, purporting to show that human subjects, incorrectly let large causes ‘overshadow’ small causes, misrepresents the most likely, and warranted, causal explanation available to the subjects, in the light of which their responses were normative; (iii) showing how a recent psychological theory (due to P. Cheng) of human judgment of causal power can be considerably generalized: and (iv) suggesting a range of possible experiments comparing human and computer abilities to extract causal information from associations.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1008234330618
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