Year: 2014
Type: article
Abstract: The purpose in diagnostic reasoning is to find the cause of observed effects by applying knowledge about the effects and their potential causes.In the causal structure linking causes and effects, effects can share causes or be linked more indirectly.The causal diversity effect reflects the increased support of a cause by a more widespread distribution of effects within the underlying causal structure.We report two experiments, in which participants acquired knowledge about causal structures and then evaluated diverse and proximal effect patterns with regard to their support for inferring a cause.The diversity effect in diagnostic reasoning was stronger if participants had acquired integrated knowledge about causal structures.Moreover, teaching a reduced structure with less nodes open to alternative causation of proximal effects decreased the diversity effect.This confirmed that the causal diversity effect results from considering alternative causation and more generally that diagnostic reasoning draws on causal representations.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
Awards: G8341507740, G8830321165
OpenAlex ID: W2768144283