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相关概念视频

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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Intelligence01:27

Intelligence

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The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
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Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

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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...
37.5K

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相关实验视频

Updated: Jun 7, 2025

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
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Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

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一个关于评估AI助理能力在叙事采访中的案例研究.

Chitat Chan1, Yunmeng Zhao1, Jiahui Zhao1

  • 1Social Work, Hong Kong Baptist University, Hong Kong, Hong Kong.

F1000Research
|November 18, 2024
PubMed
概括

这项研究探讨了AI.

科学领域:

  • 社会科学 社会科学 社会科学
  • 人工智能的人工智能
  • 人与计算机的交互

背景情况:

  • 人工智能的作用正在扩大,超越数据分析到社会研究互动.
  • 人工智能对叙事采访的影响,一种协作数据收集方法,仍然未被充分探索.
  • 有效的叙事采访需要采访者技能,如同情心和结构化的询问.

研究的目的:

  • 调查AI在进行叙事采访中的潜力.
  • 评估AI在维护面试结构,同理心和叙事质量的表现.
  • 评估基于观察的指标对评估人工智能驱动面试的非技术研究人员的有用性.

主要方法:

  • 使用WhatsApp上的OpenAI助理进行叙事采访的案例研究.
  • 一个参与者分享了一个故事两次:一次标准,一次故意偏离.
  • 通过对话分析和叙事指标 (结构,同理心,连贯性,机构支持) 评估AI表现.

主要成果:

  • 人工智能在对话中展示了适应性和结构维护.
  • 这些发现说明了AI在个性化和灵活的叙事采访方面的潜力.
  • 该研究成功测试了评估人工智能驱动叙事采访的指标.
关键词:
人工智能的人工智能交谈式人工智能 交谈式人工智能数字研究方法 数字研究方法叙述的调查 叙述的调查快速传输工程 快速传输工程定性研究是指质量研究.在WhatsApp的采访.

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结论:

  • 基于观察的指标可以帮助非技术社会研究人员评估AI访谈质量.
  • 这项研究促使人们反思人工智能在定性社会研究中的不断变化的作用.
  • 结果鼓励进一步研究用于叙事数据收集的AI应用.