NSF Convergence Accelerator Track F: Actionable Sensemaking Tools for Curating and Authenticating Information in the Presence of Misinformation during Crises
NSF Convergence Accelerator Track F: Actionable Sensemaking Tools for Curating and Authenticating Information in the Presence of Misinformation during Crises
批准号:
2137806
负责人:
Srinivasan Parthasarathy
金额:
$75.0万
依托单位:
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
项目状态:
已结题
起止时间:
2021-10-01 至 2024-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Collaborative Research: PPoSS: Planning: A Cross-Layer Observable Approach to Extreme Scale Machine Learning and Analytics
-
批准号:2028944
-
项目类别:Standard Grant
-
资助金额:$20.45万
-
财政年份:2020
-
负责人:Srinivasan Parthasarathy
-
依托单位:
EAGER: Practical Graph Sparsification on GPUs
-
批准号:1550302
-
项目类别:Standard Grant
-
资助金额:$11.12万
-
财政年份:2015
-
负责人:Srinivasan Parthasarathy
-
依托单位:
Hazards SEES: Social and Physical Sensing Enabled Decision Support for Disaster Management and Response
-
批准号:1520870
-
项目类别:Standard Grant
-
资助金额:$197.5万
-
财政年份:2015
-
负责人:Srinivasan Parthasarathy
-
依托单位:
Sampling and Inference in Network Analysis
-
批准号:1418265
-
项目类别:Standard Grant
-
资助金额:$30.0万
-
财政年份:2014
-
负责人:Srinivasan Parthasarathy
-
依托单位:
SHF:Small:Collabroative Research: Elastic Fidelity: Trading off Computational Accuracy for Energy Efficiency
-
批准号:1217353
-
项目类别:Standard Grant
-
资助金额:$18.2万
-
财政年份:2012
-
负责人:Srinivasan Parthasarathy
-
依托单位:
CCF: EAGER: Collaborative Research: Scalable Graph Mining and Clustering on Desktop Supercomputers
-
批准号:1240651
-
项目类别:Standard Grant
-
资助金额:$7.5万
-
财政年份:2012
-
负责人:Srinivasan Parthasarathy
-
依托单位:
EAGER: Towards New Scalable Stochastic Flow Algorithms
-
批准号:1141828
-
项目类别:Standard Grant
-
资助金额:$15.0万
-
财政年份:2011
-
负责人:Srinivasan Parthasarathy
-
依托单位:
SoCS: Collaborative Research: Social Media Enhanced Organizational Sensemaking in Emergency Response
-
批准号:1111118
-
项目类别:Standard Grant
-
资助金额:$27.0万
-
财政年份:2011
-
负责人:Srinivasan Parthasarathy
-
依托单位:
Global Graphs: A Middleware for Data Intensive Computing
-
批准号:0917070
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2009
-
负责人:Srinivasan Parthasarathy
-
依托单位:
Scalable Data Analysis: An Architecture Conscious Approach
-
批准号:0702587
-
项目类别:Continuing Grant
-
资助金额:$0.0万
-
财政年份:2007
-
负责人:Srinivasan Parthasarathy
-
依托单位:
SGER: An Event-Driven Approach for Analyzing Interaction Networks
-
批准号:0742999
-
项目类别:Standard Grant
-
资助金额:$0.0万
-
财政年份:2007
-
负责人:Srinivasan Parthasarathy
-
依托单位:
CAREER: A Scalable Framework for Mining Scientific and Biomedical Data
-
批准号:0347662
-
项目类别:Continuing Grant
-
资助金额:$49.78万
-
财政年份:2004
-
负责人:Srinivasan Parthasarathy
-
依托单位:
NGS: A Services-Oriented Framework for Next Generation Data Analysis Centers
-
批准号:0406386
-
项目类别:Continuing Grant
-
资助金额:$60.8万
-
财政年份:2004
-
负责人:Srinivasan Parthasarathy
-
依托单位:
海外基金