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相关概念视频

Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

479
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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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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Humanistic Psychology01:24

Humanistic Psychology

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Humanistic psychology emerged in the mid-20th century as a response to the deterministic and pessimistic nature of behaviorism and psychoanalysis. While behaviorism focused on observable behaviors influenced by the environment and psychoanalysis delved into unconscious motivations, both theories suggested that human actions lacked free will. In contrast, humanistic psychology offers a perspective that emphasizes the innate potential for goodness and growth within every individual.
This approach...
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Fundamental Attribution Error01:14

Fundamental Attribution Error

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According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
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相关实验视频

Updated: Jun 29, 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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对人工智能系统的以人为中心的解释.

C Baber1, P Kandola1, I Apperly2

  • 1School of Computer Science, University of Birmingham, Birmingham, UK.

Ergonomics
|April 8, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入以人为中心的可解释AI (XAI),以确保AI建议与用户偏好保持一致. 一个新的界面有助于用户了解他们的输入如何影响AI决策,提高对人工智能的信任和透明度.

关键词:
可解释的人工智能用户界面设计用户界面设计用户试验用户试验

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

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科学领域:

  • 人与计算机的交互
  • 人工智能伦理学 人工智能伦理学
  • 可解释的人工智能 (XAI)

背景情况:

  • 人工智能 (AI) 系统日益增长的功能引发了人们对它们对日常决策的影响的担忧.
  • 现有的可解释AI (XAI) 往往忽略了人工智能驱动的建议中关键的人类因素.
  • 人工智能系统需要透明,能够响应个人用户的需求和偏好.

研究的目的:

  • 正式定义以人为中心的可解释AI (XAI).
  • 设计和评估一个用户界面,以促进用户偏好输入和与AI建议进行比较.
  • 提高用户对人工智能决策过程及其影响的理解.

主要方法:

  • 以人为中心的XAI原则的正式定义.
  • 开发一个用户界面,用于偏好指示和比较.
  • 进行用户试用,以评估界面的有效性.

主要成果:

  • 用户可以在界面中有效地表明他们的偏好.
  • 用户试验表明,参与者理解他们的偏好如何影响AI建议.
  • 用户还可以欣赏他们的偏好和人工智能系统的偏好之间的对比.

结论:

  • 拟议的以人为中心的XAI方法提高了用户对AI建议的理解.
  • 开发的用户界面有效地支持用户参与和AI系统的透明度.
  • 为实施以人为中心的XAI提供了指导方针,以培养更值得信赖的AI.