NSF Convergence Accelerator Track F: Actionable Sensemaking Tools for Curating and Authenticating Information in the Presence of Misinformation during Crises

NSF 融合加速器轨道 F：危机期间存在错误信息时用于整理和验证信息的可行的意义建构工具

• 批准号: 2137806
• 负责人: Srinivasan Parthasarathy
• 金额: $ 75万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137806&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Actionable

High volume, rapidly changing, diverse information, which often includes misinformation, can easily overwhelm decision makers during a crisis. Decisions made both during and long after a crisis, affect the trust between responsible decision makers and citizens (many from vulnerable populations), who are impacted by those decisions. This project seeks to help decision makers manage information, promoting reliance on authentic knowledge production processes while also reducing the impact of intentional disinformation and unintended misinformation. The project team will develop a suite of prototype tools that bring timely, high-quality integrated content to bear on decision making and governance, as a routine part of operations, and especially during a crisis. Integrated and authenticated content comprising scientific facts and technical information coupled with citizen and stakeholder viewpoints assure the accuracy of safety decisions and the appropriate prioritization of relief efforts. The project team will synthesize convergent expertise across multiple disciplines; engage and build stakeholder communities through partnerships with government and industry to guide tool development; build a prototype tool for authenticating data and managing misinformation; and validate the tool using real world crisis scenarios.The project team will create use-inspired personalized AI-driven sensemaking prototype tools for decision-makers to comprehend and authenticate dynamic, uncertain, and often contradictory information to facilitate effective decisions during crises. The tools will focus on curation while accounting for source and explainable content credibility. Guidance from community stakeholders obtained using ethnographic methods will ensure that the resulting tools are practical, timely, and relevant for informed decision making. These tools will capitalize on features of the information environment, human cognitive abilities and limitations, and algorithmic approaches to managing information. In particular, content and network analyses can reveal constellations of sources with a higher probability of producing credible information, while knowledge graphs can help surface and organize important materials being shared while facilitating explainability. The project team will also design and develop a microworld environment to examine and improve tool robustness while simultaneously helping to train decision makers in real-world settings such as school districts and public health settings. This project represents a convergence of disciplines spanning expertise in computer science, social sciences, linguistics, network science, public health, cognitive science, operations, and communication that are necessary to achieve its goals. Partnerships between communities, government industry, and academia will ensure the deliverables are responsive to stakeholder needs.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.

在危机期间，大量、快速变化、多样化的信息（其中往往包括错误信息）很容易使决策者不知所措。 在危机期间和危机后很长一段时间内作出的决定会影响负责任的决策者与公民（许多来自弱势群体）之间的信任，而公民又会受到这些决定的影响。该项目旨在帮助决策者管理信息，促进对真实知识生产过程的依赖，同时减少故意虚假信息和无意错误信息的影响。项目小组将开发一套原型工具，为决策和治理提供及时、高质量的综合内容，作为业务的一个常规部分，特别是在危机期间。综合和认证的内容包括科学事实和技术信息，加上公民和利益攸关方的观点，确保安全决策的准确性和救灾工作的适当优先次序。该项目小组将综合多个学科的趋同专门知识;通过与政府和行业的伙伴关系参与和建立利益攸关方社区，以指导工具开发;建立一个用于认证数据和管理错误信息的原型工具;并使用真实的世界危机场景验证该工具。项目团队将创建用于决策的个性化人工智能驱动的感知原型工具，决策者需要理解和验证动态的、不确定的、往往相互矛盾的信息，以促进危机期间的有效决策。这些工具将专注于策展，同时考虑来源和可解释内容的可信度。使用人种学方法获得的社区利益相关者的指导将确保所产生的工具是实用的，及时的，并与知情决策相关。这些工具将利用信息环境的特点、人类的认知能力和局限性以及管理信息的算法方法。特别是，内容和网络分析可以揭示来源的星座，更有可能产生可信的信息，而知识图可以帮助揭示和组织共享的重要材料，同时促进解释。该项目团队还将设计和开发一个微观世界环境，以检查和提高工具的鲁棒性，同时帮助培训现实环境中的决策者，如学区和公共卫生环境。该项目代表了跨越计算机科学，社会科学，语言学，网络科学，公共卫生，认知科学，运营和通信专业知识的学科融合，这些学科是实现其目标所必需的。社区、政府行业和学术界之间的伙伴关系将确保交付成果能够满足利益相关者的需求。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。