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Related Concept Videos

Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Stereotype Threat and Self-fulfilling Prophecies02:09

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When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
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Stereotypes, Prejudice, and Discrimination02:55

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Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
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Implicit personality theory explains how individuals make assumptions about the relationships between personality traits, behaviors, and character types. When people learn that someone possesses a particular trait, they tend to infer the presence of other related characteristics, forming a cohesive impression. This cognitive shortcut plays a crucial role in social interactions and interpersonal judgments.Central Traits and Their InfluenceSolomon Asch's seminal 1946 study highlighted the power...
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The Representativeness Heuristic02:13

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The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
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Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...
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Updated: Jan 16, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

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Stereotypes in artificial intelligence-generated content: Impact on content choice.

Fei Gao1, Lan Xia1, Wenting Zhong1

  • 1Department of Marketing, Bentley University.

Journal of Experimental Psychology. Applied
|September 29, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) image generators like ChatGPT and Midjourney replicate and amplify sex and racial stereotypes. Reducing stereotypical AI content decreases biased choices, but awareness alone doesn't prevent selection of harmless stereotypes.

Related Experiment Videos

Last Updated: Jan 16, 2026

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07:34

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Area of Science:

  • Artificial Intelligence
  • Social Psychology
  • Media Studies

Background:

  • Generative artificial intelligence (AI) is increasingly used for content creation.
  • A significant concern is the potential for AI to propagate and amplify societal stereotypes.

Purpose of the Study:

  • To investigate whether AI image generators replicate and amplify sex and racial stereotypes.
  • To examine how the availability of stereotypical AI-generated content influences user choices and beliefs.
  • To assess the impact of awareness on self-correction regarding AI-generated stereotypes.

Main Methods:

  • A large-scale field study (2024) involving AI image generators (ChatGPT, Midjourney, Canva) creating 1,110 images.
  • Five preregistered experiments (2024-2025) with 2,994 U.S. adults.
  • Analysis of choice sets, user selections, and impact of stereotype awareness.

Main Results:

  • AI systematically replicates and amplifies sex and racial stereotypes by offering more stereotypical content in choice sets.
  • Increased availability of stereotypical AI content leads to higher likelihood of selection, driven by availability and pre-existing biases.
  • Awareness of AI stereotypes does not reduce selection of "harmless" stereotypes but can lead to self-correction for "harmful" stereotypes.

Conclusions:

  • AI image generation tools can perpetuate and exacerbate societal biases.
  • Interventions reducing the availability of stereotypical AI content can mitigate biased choices and beliefs.
  • The perceived harm of a stereotype influences whether awareness prompts self-correction.