Explanation of Probabilistic Inference for Decision Support Systems
  An automated explanation facility for Bayesian conditioning aimed at
improving user acceptance of probability-based decision support systems has
been developed. The domain-independent facility is based on an information
processing perspective on reasoning about conditional evidence that accounts
both for biased and normative inferences. Experimental results indicate that
the facility is both acceptable to naive users and effective in improving
understanding.
