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Language and Cognition01:27

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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.
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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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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Language Development01:22

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Updated: Sep 13, 2025

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Artificial Intelligence Is Stereotypically Linked More with Socially Dominant Groups in Natural Language.

Zixi Wang1,2, Haodong Xia1,2, Han Wu Shuang Bao3

  • 1State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
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Artificial intelligence (AI) is perceived as highly competent but is disproportionately associated with advantaged social groups. This bias may reinforce existing societal inequalities and create an "AI divide."

Keywords:
artificial intelligencenatural language processingsocial representationstereotype

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Area of Science:

  • Social Psychology
  • Artificial Intelligence Studies
  • Sociology of Technology

Background:

  • Artificial intelligence (AI) plays a crucial societal role, yet its social representation is under-researched.
  • Understanding public perception of AI is vital for equitable societal integration.

Purpose of the Study:

  • To investigate the social representation of AI, specifically its associations with warmth and competence.
  • To examine AI's connections with socially advantaged versus disadvantaged demographic groups.
  • To analyze AI's perceived impact on high- versus low-prestige occupations.

Main Methods:

  • Utilized language-based analyses with static word embeddings, BERT, and GPT-4o across four studies.
  • Incorporated human-participant experiment validation for robust findings.
  • Applied the stereotype content model to assess warmth-competence dimensions.

Main Results:

  • AI is strongly linked to high competence, with variable warmth associations.
  • AI demonstrates closer semantic links to advantaged demographic groups (e.g., men, white, rich).
  • High-prestige occupations are more strongly associated with AI's benefits than low-prestige ones.

Conclusions:

  • Public perception of AI is systematically biased towards socially dominant groups.
  • This bias may exacerbate existing social inequalities.
  • Findings highlight concerns regarding an emerging