A constraint satisfaction neural network model (the consonance model)
simulated data from the two major cognitive dissonance paradigms of in
sufficient justification and free choice. In several cases, the model
fit the human data better than did cognitive dissonance theory. Superi
or fits were due to the inclusion of constraints that were not part of
dissonance theory and to the increased precision inherent to this com
putational approach. Predictions generated by the model for a free cho
ice between undesirable alternatives were confirmed in a new psycholog
ical experiment. The success of the consonance model underscores impor
tant, unforeseen similarities between what had been formerly regarded
as the rather exotic process of dissonance reduction and a variety of
other, more mundane psychological processes. Many of these processes c
an be understood as the progressive application of constraints supplie
d by beliefs and attitudes.