The representativeness heuristic is a mental process characterized by using prototypes as short-cut rules for classifying information and objects. Thus, we look for similarity between the information perceived and a prototype stored in memory. If the information seems to fit the prototype somehow, we tend to classify the information or object as a member of the class represented by the prototype (Passer & Smith, 20091).
The main problem with this heuristic is that it may lead to logical errors when classifying information and objects, with further consequences of making bad decision because of those logical errors. The reason behind those logical errors seems to be that we tend to confuse representativeness with probability. That is, because some information or an object seems to be more representative of a particular class, we tend to assume it is more probable, as well (Passer & Smith, 20091).