SBE-UKRI: A Novel Theory of Ordered Judgment Processes

SBE-UKRI：有序判断过程的新颖理论

• 批准号: 2343580
• 负责人: Stephen Broomell
• 金额: $ 59.01万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2343580&HistoricalAwards=false
• 关键词: SBE; UKRI; Novel; Theory; Ordered

Difficult decisions are commonplace, yet often require decision makers to gather information from disparate places and combine it to make conclusions. For example, when choosing whether to have a risky, but potentially needed, medical procedure, a patient may need to consult several doctors that have different specializations, knowledge, and backgrounds, leaving the patient to aggregate this information and determine a course of action. This interdisciplinary research explores how to support individuals, organizations and governments in making better decisions through a novel approach that explores the way decision-making and information are interrelated. Decisions are shaped not only by how individuals weigh information, but also by how they weigh the information sources, such as who exactly is providing this information. Through blending advances in psychology and computer science, the project seeks to explain previously unexplainable behavior and better predict judgments in new situations. Such knowledge can facilitate decision support systems across many domains. Additionally, this research holds the potential to reveal new pathways towards translating complex artificial intelligence (AI) systems into a form that is more compatible with human cognitive processes. The project proposes a new theory of judgment that fuses psychological theory with operational and theoretical advances from computer science in the areas of data aggregation and artificial intelligence. The theory of ordered judgment provides the first operational framework for empirical tests of the role of ordering in judgment and beyond, and impacts both psychological and computer science research. For psychology, the theory of ordered judgment has many implications for how to display data to facilitate accurate processing that can be useful for decision-support and human factors work in contexts ranging from graphical user interfaces to operating machinery. For computer science, this work contributes to the crucial area of explainable artificial intelligence by articulating direct links between complex computer algorithms and human reasoning. This can afford mechanisms to understand, evaluate and validate AI driven decision-making approaches in critical applications such as security and defense, energy, and healthcare.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

艰难的决策是司空见惯的，但通常要求决策者从不同地方收集信息并结合起来以得出结论。例如，在选择是否有风险但可能需要的医疗程序时，患者可能需要咨询几位具有不同专业，知识和背景的医生，使患者可以汇总此信息并确定行动方案。这项跨学科研究探讨了如何通过一种新颖的方法来支持个人，组织和政府来做出更好的决策，从而探讨决策和信息相互关联的方式。决策不仅是由个人称重信息的方式来塑造的，而且还取决于他们如何权衡信息来源，例如谁确切地提供了此信息。通过融合心理学和计算机科学的进步，该项目试图解释以前无法解释的行为，并更好地预测新情况下的判断。这种知识可以促进许多领域的决策支持系统。此外，这项研究具有揭示将复杂人工智能（AI）系统转化为与人类认知过程更兼容的形式的新途径。该项目提出了一种新的判断理论，该理论将心理理论与计算机科学的运作和理论进步融合在一起，在数据聚合和人工智能领域。有序判断的理论为有序作用在判断及其他方面的作用提供了第一个操作框架，并影响了心理和计算机科学研究。对于心理学，有序判断的理论对如何显示数据以促进准确的处理具有许多影响，这对决策支持很有用，并且人为因素在从图形用户界面到操作机械等上下文中起作用。对于计算机科学，这项工作通过阐明复杂的计算机算法与人类推理之间的直接联系来为可解释的人工智能的关键领域。这可以提供理解，评估和验证AI驱动的决策方法（例如安全与国防，能源和医疗保健）中的机制。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准通过评估来进行评估的。