Computer-mediated Counter-Arguments and Individual Learning

This study explores a de-bias function for a decision support systems (DSS) that is designed to help a user avoid confirmation bias by increasing the user’s learning opportunities. Grounded upon the theory of mental models, the use of DSS is viewed as involving a learning process, whereby a user is directed to build mental models so as to reduce the tendency to consider only data that supports any preexisting mental models. The results of an experiment suggest that a de-bias function, called computer-mediated counter-argument (CMCA), facilitates individual learning and improves decision satisfaction.