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CyberSEES:Type 2: Collaborative Research: Combining Experts and Crowds to Address Challenging Societal Problems

CyberSEES:Type 2: Collaborative Research: Combining Experts and Crowds to Address Challenging Societal Problems
Cyber​​SEES:类型 2:协作研究:将专家和大众结合起来解决具有挑战性的社会问题
批准号:
1442887
负责人:
Thomas Malone
金额:
$59.89万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-01-15 至 2018-12-31

项目摘要

项目成果

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中文摘要
翻译
从编写百科全书,到开发软件,再到折叠蛋白质,越来越多的问题过去是由一小群专家解决的,现在则是由更大规模的“群体”使用互联网来解决。然而,对于许多复杂的问题,群体带来的创造力、能量和多样性不足以解决问题。还需要各种只有专家才具备的专业知识。该项目的重点是建立网络基础设施,以便将专家和群众这两种资源联合收割机结合起来,解决复杂的社会问题。该项目将在许多人认为是人性的背景下解决这个问题?当今最重要的可持续发展挑战:如何应对环境动态趋势。大部分拟议的工作包括在团队的CoLab上开发和测试想法,CoLab是一个专注于这个问题的软件平台和在线社区,它是在之前的NSF和其他支持下开发的。 更具体地说,该项目将研究专家和群体如何共同努力,执行四个关键的问题解决活动:将整体问题分解为较小的部分,为部分生成潜在的解决方案,将部分整合为整体解决方案,并评估解决方案。例如,该项目将研究(a)当群体从专家的“种子”想法开始时,他们是否会产生更好的想法,(B)如何将某些类型的专家知识编码到群体可以自己使用的计算机模拟模型中,以及(c)半专家、新手和软件工具的组合在多大程度上可以近似专家的评估。 预计成果将包括:(a)适用于许多可持续性和其他挑战的开放源码软件;(B)一套流程和方法,使社区能够有效地使用这一软件;(c)一个由数万人组成的多样化社区,使用这一方法来解决与环境变化趋势有关的问题。 拟议的工作的主要智力贡献将是更好的过程和计算机工具,用于创建联合收割机结合专家和群众的最佳功能来解决复杂的社会问题的在线社区。要研究的技术和组织方法的许多方面应该是感兴趣的研究人员在各个领域,包括集体智慧,计算机支持的合作工作,人机交互,计算机科学,工程,组织设计,心理学和公共政策。 通过让学生和公众参与进来,就人们如何处理复杂问题提出可信的想法,该项目将有助于教育更广泛的社区了解所涉及的实际问题。如果成功的话,这项工作将可能导致为复杂的社会问题制定更好的方法,而不是制定任何其他方法。结果的许多方面将适用于广泛的领域,如教育,医疗保健和商业问题,如战略规划和预算。
英文摘要
From writing an encyclopedia, to developing software, to folding proteins, more and more problems that used to be solved by small groups of experts are now being solved by much larger "crowds" of people using the Internet. For many complex problems, however, the creativity, energy, and diversity that crowds bring are not enough to solve the problems. Various kinds of specialized knowledge that only experts have are also needed. This project focuses on creating the cyber-infrastructure to combine these two kinds of resources--experts and crowds--in solving complex societal problems. The project will address this question in the context of what many people believe is one of humanity?s most important sustainability challenges today: how to deal with trending environmental dynamics. Much of the proposed work includes developing and testing ideas on the team's CoLab, a software platform and online community focused on this issue, which was developed with prior NSF and other support. More specifically, the project will investigate how experts and crowds can work together to perform four key problem-solving activities: decomposing the overall problem into smaller pieces, generating potential solutions for the pieces, integrating the pieces into overall solutions, and evaluating the solutions. For example, the project will study (a) whether crowds generate better ideas when they start with "seed" ideas from experts, (b) how certain kinds of expert knowledge can be encoded in computer simulation models that crowds can use on their own, and (c) to what degree expert evaluations can be approximated by combinations of semi-experts, novices, and software tools. The results are expected to include (a) open source software applicable to many sustainability and other challenges, (b) a set of processes and methodologies with which communities can effectively use this software, and (c) a diverse community of tens of thousands of people using this approach to address issues associated with trending environmental changes. The primary intellectual contribution of the proposed work will be better processes and computer tools for creating on-line communities that combine the best features of both experts and crowds to solve complex societal problems. Many aspects of the technical and organizational approaches to be studied should be of interest to researchers in a variety of fields, including collective intelligence, computer-supported cooperative work, human computer interaction, computer science, engineering, organizational design, psychology, and public policy. By engaging students and the general public to come up with credible ideas for what people can do about complex problems, this project will help educate a much broader community about the actual issues involved. If successful, the work will likely lead to the development of better approaches for complex societal problems than any that would otherwise have been developed. Many aspects of the results will be applicable to a wide range of domains such as education, healthcare, and business problems like strategic planning and budgeting.
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会议论文
VOSS: Collaborative Research: Is Larger Smarter? Investigating the Effect of Group Size on Collective Intelligence
EAGER: The Climate CoLab: A System for Very Large-Scale Model-Based Group Problem-Solving
Workshop on Collective Intelligence
SoCS: The Climate Collaboratorium: A Tool for Large-Scale Model-Centric Collective Decision-Making
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