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相关概念视频

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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Ethics is a philosophical study of moral actions. Ethics attempts to determine what is valuable for individuals and society. It examines the rational justification of moral judgments and analyzes what is morally just, fair, and right. Bioethics is a sub-discipline of applied ethics that analyzes the philosophical, social, and legal issues in life sciences and medicine. Ethical theories serve as a foundation for decision-making and represent the viewpoints from which people seek direction. They...
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Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
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Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:
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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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一个超知识图表系统用于研究AI伦理案例.

Chuan Chen1, Yu Feng1, Mengyi Wei1

  • 1Chair of Cartography and Visual Analytics, Technical University of Munich, Munich, Germany.

Heliyon
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概括
此摘要是机器生成的。

本研究引入了以案例为导向的本体模型 (COOM) 和超知识图系统 (HKGS),以解决当前人工智能 (AI) 伦理研究的局限性. 这些工具可以为AI伦理案件提供可操作的见解和跨领域的可转移性.

关键词:
人工智能伦理学以案例为导向的存在学模型超知识图表系统的超知识图表系统.基于知识的系统是基于知识的系统.视觉分析 视觉分析

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科学领域:

  • 计算机科学 计算机科学
  • 伦理学 伦理学 伦理学
  • 信息科学 信息科学 信息科学

背景情况:

  • 目前的人工智能 (AI) 伦理研究往往缺乏实际应用,原因是过于广泛的指导方针或狭窄的领域重点.
  • 现有的研究未能在不同级别的细节上探索AI伦理案例之间的相关性,这阻碍了知识转移.
  • 需要一种结构化的方法来建模和分析人工智能伦理案例,以便更好地理解和应用.

研究的目的:

  • 开发一种新的以案例为导向的本体模型 (COOM) 来构建AI伦理案例.
  • 创建一个超知识图表系统 (HKGS) 来存储和分析AI伦理案例之间的相关性.
  • 为了使人工智能伦理案例相互依赖性及其在价值链中的演变能够进行先进的视觉分析.

主要方法:

  • 设计了一个以案例为导向的本体模型 (COOM),具有事件,关系和位置属性.
  • 开发了一个超知识图表系统 (HKGS) 来存储和可视化AI伦理案例之间的相关性.
  • 使用样本AI伦理案例实现HKGS,以展示图形生成和视觉分析.

主要成果:

  • COOM提供了一个标准化的框架,用于模拟各种AI伦理案例.
  • 在AI伦理案例中,HKGS有效地存储和可视化复杂的关系和动态变化.
  • 展示了HKGS在分析特定的人工智能伦理场景方面的实际实用性.

结论:

  • 拟议的COOM和HKGS为弥合人工智能伦理理论和实践之间的差距提供了一个强有力的解决方案.
  • 香港学术研究促进了对人工智能伦理案例相关性的更深入的理解,促进了跨领域的知识转移.
  • 该系统为各种AI伦理学从业者提供了信息决策和情景探索的工具.