ITR: Managing human attention

ITR：管理人类注意力

• 批准号: 0325351
• 负责人: Robert Kraut
• 金额: $ 200万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-11-01 至 2008-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0325351&HistoricalAwards=false
• 关键词: ITR; Managing; human; attention

Since at least the early 1900s, the supply of information and communication has been growing faster than our ability to consume it. From the information producers' viewpoint, much information is wasted, in the sense that it doesn't reach those to whom it is relevant. For the consumer, the glut of information makes it increasingly difficult to find what is relevant, useful or enjoyable. This "poverty of attention" also occurs in the domain of interpersonal communication, where informal and spontaneous interaction, a hallmark of managerial and professional work, generates interruptions and overload. In this project, the PI and his team will develop, integrate and use principles from social psychology, computer science, economics, and interaction design to devise ways of economizing on attention in a communication rich environment. Specifically, they will develop, deploy and evaluate techniques to mediate among the often competing demands of responding to a barrage of communication requests that compete for attention when performing a primary task, such as driving a car or interviewing a client. To do so, the PI team will use sensing technology and machine learning techniques to identify a worker's current task and degree of interruptibility. They will display team members' availability to a subset of communication partners and use principles developed in economics and social psychology to balance the competing demands on the worker's attention. They will also use principles developed in interaction design to build lightweight, peripheral displays and context-aware interaction techniques that allow people to briefly and simply comprehend information without disrupting their primary task. Although the principles and techniques developed will be applicable across many domains, this project will make use of a specific context for development and testing, namely improving communication efficiency of mobile health care workers caring for the elderly. The PI team consists of a social psychologist, a computer scientist, and a designer, who have been working previously both individually and jointly on problems of human attention; part of this project will involve integrating results from research efforts already underway. Broader Impacts: Issues of managing attention and information overload are pervasive in our increasingly connected and technological society. Development of principles and specific techniques for addressing these issues has the potential for large benefit and widespread impact beyond the eldercare domain. In addition, support for the project's target domain - mobile eldercare workers - offers the potential of direct social benefit to a rapidly aging population. The project will lead to better understanding of design principles for economizing on attention, to prototype development, and to lab and field testing of the models, all of which will help save on the most precious of human resources - our attention.

至少自 1900 年代初以来，信息和通信供应的增长速度快于我们消费能力的增长速度。 从信息生产者的角度来看，很多信息都被浪费了，因为它没有到达相关的人手中。 对于消费者来说，信息过剩使得他们越来越难以找到相关、有用或令人愉悦的信息。 这种“注意力匮乏”也发生在人际交往领域，非正式和自发的互动是管理和专业工作的标志，但会造成干扰和超负荷。 在这个项目中，PI 和他的团队将开发、整合和使用社会心理学、计算机科学、经济学和交互设计的原理，设计出在交流丰富的环境中节省注意力的方法。 具体来说，他们将开发、部署和评估技术，以在经常相互竞争的需求之间进行调解，以响应在执行主要任务（例如驾驶汽车或采访客户）时争夺注意力的一系列通信请求。 为此，PI 团队将使用传感技术和机器学习技术来识别工人当前的任务和可中断程度。 他们将向一部分沟通伙伴展示团队成员的可用性，并使用经济学和社会心理学中发展的原理来平衡对员工注意力的竞争需求。 他们还将使用交互设计中开发的原理来构建轻量级外围显示器和上下文感知交互技术，使人们能够在不中断其主要任务的情况下简单地理解信息。 尽管开发的原理和技术将适用于许多领域，但该项目将利用特定的环境进行开发和测试，即提高照顾老年人的移动医护人员的通信效率。 PI 团队由一名社会心理学家、一名计算机科学家和一名设计师组成，他们之前一直单独或共同研究人类注意力问题；该项目的一部分将涉及整合已经进行的研究工作的成果。更广泛的影响：在我们日益互联和技术化的社会中，管理注意力和信息过载的问题普遍存在。 制定解决这些问题的原则和具体技术可能会在老年护理领域之外产生巨大的效益和广泛的影响。 此外，对该项目的目标领域——流动老年护理人员——的支持为快速老龄化的人口提供了直接社会效益的潜力。 该项目将有助于更好地理解节省注意力的设计原则、原型开发以及模型的实验室和现场测试，所有这些都将有助于节省最宝贵的人力资源——我们的注意力。