
Broadly speaking, stereotypes are features perceived to be associated with particular categories of people, and stereotyping corresponds to the characterisation of a group of people as sharing the same behaviours and attributes. According to the economic approach, stereotypes are beliefs about a group member in terms of the aggregate statistical distribution of group traits. In the sociological approach, stereotypes are described as oversimplified, derogatory and fundamentally incorrect generalisations about social groups. Finally, in the social cognition approach, stereotypes are seen as special cases of cognitive schemas: limited-capacity human minds create shortcuts via judgmental heuristics that result in savings on cognitive resources. These judgments are based on data of limited validity, processed according to heuristic rules, that might lead to biased conclusions. More recently, the investigation of stereotype formation and function has been explored in the framework of Bayesian predictive processing. Learning for the predictive brain involves testing predictions by using the data obtained from the world and applying Bayes’ theorem to develop probabilities. According to this learning process, instead of conceptualising stereotypes as a problem of the cognitive bias of the individual, it can be sustained that they should be viewed as “culture in mind”, influencing the cognition of cultural group members. In this talk, I will discuss statistical aspects of the stereotyping process and its biases and present some results of our research on stereotypes.