Stereotyping refers to the belief that certain characteristics are characteristic of a group of elements. This belief may be well-founded or may be partly unfounded. Most stereotypes are also characterized by generalization, which means that individual differences between the elements or group members are ignored or marginalized.

This mental strategy helps to reduce complexity and enables us to make quick decisions in social interactions. From an evolutionary psychological point of view, this ability was crucial to quickly distinguish between friend and foe in potentially dangerous situations and to react appropriately. Such quick judgments increased the chances of survival for our ancestors in an unsafe and threatening environment.

Human cognition is geared towards processing information efficiently. The formation of stereotypes simplifies complex social circumstances, enabling them to be processed more quickly. The tendency to categorize is also deeply rooted in our cognitive processes and reflects the need to organize the multitude of daily impressions and make them manageable.

However, simplifications and categorizations can also lead to distortions that are problematic in modern societies because they can contribute to prejudice and discrimination.

Origin

The term was first used in 1922 by the American journalist Walter Lippmann to describe the "images in our heads" that "slip between our external world and our consciousness as the content of our imagination".

  • Lippmann, W. (1922). Public Opinion. Harcourt, Brace and Company.
  • Allport, G. W. (1954). The Nature of Prejudice. Addison-Wesley.
  • Tajfel, H. (1979). Individuals and Groups in Social Psychology. British Journal of Social and Clinical Psychology, 18(2), 183–190.

Other biases support stereotyping, in particular:

Application in UX and UI design

Stereotyping can unintentionally influence user decisions in UX and UI design. One example is the design of personas, where it is important not only to avoid clichéd or stereotypical representations, but also to take a differentiated look at real user needs. If personas are based only on superficial characteristics such as gender, age or ethnic origin, for example, this can lead to false assumptions about user behavior and to designs that fail to meet actual user needs.

Another example is personalization in algorithms: when systems suggest certain content or products to users based on stereotypical assumptions, this can lead to a Confirmation Bias in which people only see what reinforces their existing beliefs. Responsible use of algorithms therefore requires that systems recognize diverse patterns and not just reinforce stereotypical assumptions.

Impact on the User Experience

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Further information