SBE-UKRI: A Novel Theory of Ordered Judgment Processes

困难的决策是司空见惯的，但往往需要决策者从不同的地方收集信息，并联合收割机作出结论。例如，当选择是否进行有风险但可能需要的医疗程序时，患者可能需要咨询具有不同专业，知识和背景的几位医生，让患者汇总这些信息并确定行动方案。这项跨学科的研究探讨了如何支持个人，组织和政府通过探索决策和信息相互关联的方式的新方法做出更好的决策。决策不仅取决于个人如何权衡信息，还取决于他们如何权衡信息来源，例如谁提供了这些信息。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。这些知识可以促进跨许多领域的决策支持系统。此外，这项研究有可能揭示将复杂的人工智能（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，将心理学理论与计算机科学在数据聚合和人工智能领域的操作和理论进步相融合。有序判断理论为实证检验有序在判断中的作用提供了第一个可操作的框架，并影响了心理学和计算机科学的研究。对于心理学来说，有序判断理论对如何显示数据以促进准确处理有许多影响，这些数据可以用于决策支持和人为因素，从图形用户界面到操作机器。对于计算机科学来说，这项工作通过阐明复杂的计算机算法和人类推理之间的直接联系，为可解释的人工智能的关键领域做出了贡献。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.