Human Causal Discovery

نویسندگان

  • Ahmad I. Hashem
  • Gregory F. Cooper
چکیده

Utilizing Bayesian beliefnetworks as a model of causality, we examined medical students' ability to discover causal relationships from observational data. Nine sets ofpatient cases were generatedfrom relatively simple causal beliefnetworks by stochastic simulation. Twenty participants examined the data sets and attempted to discover the underlying causal relafionships. Performance was poor in general, except at discovering the absence ofa causal relationship. This work supports the potentialfor combining human and computer methods for causal discovery.

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تاریخ انتشار 2007