Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Stereotype Content Model

Stereotype Content Model

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...

Stereotypes, Prejudice, and Discrimination

Stereotypes, Prejudice, and Discrimination

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...

Stereotype Threat and Self-fulfilling Prophecies

Stereotype Threat and Self-fulfilling Prophecies

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...

Generalization, Discrimination, and Extinction

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...

Language and Cognition

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

Components of Language

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Social-Environmental Constraints on the Development of a Concealable Stigmatized Identity Predict Psychological Distress.

Personality & social psychology bulletin·2025

Same author

ChatGPT as Research Scientist: Probing GPT's capabilities as a Research Librarian, Research Ethicist, Data Generator, and Data Predictor.

Proceedings of the National Academy of Sciences of the United States of America·2024

Same author

Unconstrained Descriptions of Facebook Profile Pictures Support High-Dimensional Models of Impression Formation.

Personality & social psychology bulletin·2024

Same author

Extracting intersectional stereotypes from embeddings: Developing and validating the Flexible Intersectional Stereotype Extraction procedure.

PNAS nexus·2024

Same author

Valence biases and emergence in the stereotype content of intersecting social categories.

Journal of experimental psychology. General·2023

Same author

A spontaneous stereotype content model: Taxonomy, properties, and prediction.

Journal of personality and social psychology·2022

Search research articles

Related Experiment Video

Updated: Jun 6, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Directionality and representativeness are differentiable components of stereotypes in large language models.

Gandalf Nicolas¹, Aylin Caliskan²

¹Department of Psychology, Rutgers University, New Brunswick, NJ 08873, USA.

|November 26, 2024

Summary

This study introduces representativeness as a new way to understand stereotypes in AI, finding it

Keywords:

bias in Artificial Intelligence fairness in machine learning natural language processing social psychology stereotypes

More Related Videos

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Related Experiment Videos

Last Updated: Jun 6, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Area of Science:

Artificial Intelligence
Computational Social Science
Psychology

Background:

Existing AI bias research focuses on stereotype direction (e.g., competence vs. incompetence).
Representativeness, the focus of stereotypes on specific content dimensions (e.g., Warmth, Competence), remains underexamined.
Direction-based bias detection may miss representativeness biases in AI models.

Purpose of the Study:

To investigate representativeness as an independent property of stereotypes in AI models.
To examine if representativeness is distinct from stereotype direction for Warmth and Competence dimensions.
To assess the impact of representativeness and direction on AI model valence and human stereotypes.

Main Methods:

Analyzed stereotypes in ChatGPT and SBERT language models using a large sample of social categories.
Focused on the Warmth and Competence stereotype dimensions.
Examined representativeness across social category terms and racialized name exemplars.

Main Results:

Provided evidence for the construct differentiability of direction and representativeness for Warmth and Competence stereotypes.
Demonstrated these findings across different AI models and target stimuli.
Showed that both direction and representativeness uniquely predicted AI valence and human stereotypes.

Conclusions:

Representativeness is a distinct and important feature of AI stereotypes, separate from direction.
AI bias auditing needs to consider both stereotype direction and representativeness for fairness.
Findings have implications for AI in cognitive science and AI fairness research.