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相关概念视频

Stereotype Content Model02:16

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 categorization, a person will feel...
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

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 Vincent in...
Components of Language01:24

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. “eh”). Phonemes combine to...
Language Development01:22

Language Development

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.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
Language and Cognition01:27

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.
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...

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相关实验视频

Updated: Jun 14, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

从语言体中自动衍生出的语义含有类似人类的偏见

Aylin Caliskan1, Joanna J Bryson1,2, Arvind Narayanan1

  • 1Center for Information Technology Policy, Princeton University, Princeton, NJ, USA. aylinc@princeton.edu jjb@alum.mit.edu arvindn@cs.princeton.edu.

Science (New York, N.Y.)
|April 15, 2017
PubMed
概括
此摘要是机器生成的。

在网络文本上训练的机器学习模型复制隐含关联测试中发现的人类语义偏见. 这揭示了历史偏见如何嵌入语言数据,提供了识别和解决技术文化偏见的方法.

更多相关视频

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

相关实验视频

Last Updated: Jun 14, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

科学领域:

  • 人工智能
  • 自然语言处理
  • 计算社会科学

背景情况:

  • 机器学习 (ML) 通过识别数据中的模式来获得人工智能.
  • 人类语言体包含隐含的社会偏见.
  • 隐性关联测试 (IAT) 测量了概念之间的自动关联的强度.

研究的目的:

  • 研究在人类语言上训练的机器学习模型是否表现出类似人类的语义偏见.
  • 确定ML模型是否可以复制IAT测量的偏差.
  • 探索 ML 在识别和缓解文化偏见方面的潜力.

主要方法:

  • 将统计机器学习模型应用于来自万维网的大量文本.
  • 在标准文本数据上训练模型.
  • 评估模型的语义关联与已知的人类偏见,包括IAT测量的偏见.

主要成果:

  • ML模型复制了一系列人类语义偏差,反映了IAT的结果.
  • 在各种领域观察到偏见,包括道德中立 (昆虫,花),有问题的 (种族,性别) 和真实的 (性别和职业/名字).
  • 文本体准确地印记了人类的历史偏见,

结论:

  • 在真实世界的文本数据上训练的机器学习模型继承并反映人类的语义偏见.
  • 文本数据作为历史偏差的存储库,可以使用ML量化.
  • 开发的方法为发现和解决文化和技术偏见提供了有希望的方法.