SCC-CIVIC-PG Track B: Assessing the Feasibility of Systematizing Human-AI Teaming to Improve Community Resilience

SCC-CIVIC-PG 轨道 B：评估系统化人类与人工智能协作以提高社区复原力的可行性

基本信息

批准号：
2043522
负责人：
Keri Stephens
金额：
$ 4.99万
依托单位：
University of Texas at Austin
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：
2021-01-15 至 2022-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2043522&HistoricalAwards=false
关键词：
SCC CIVIC PG Track Assessing

项目摘要

Emergency managers need access to the right data to effectively and efficiently plan for and respond to disasters. Social media offers a data source that is increasingly relevant for disaster management, but emergency response organizations typically lack capacity to monitor and mine social media data at scale. One remedy is to pair human volunteers, who label relevant information, with computers to train and update artificial intelligence (AI) systems for scalable monitoring. Including local volunteers in the process is important because they are uniquely capable of identifying locally-relevant images, text, and conversations that reflect their communities. Yet, we currently have no mechanism to systematically pair these human volunteer/AI-systems with emergency management organizations. Therefore, the fundamental issue this project investigates is the feasibility of leveraging the strengths of local members of a Community Emergency Response Team (CERT) with AI—called human-AI teaming—to bridge this gap. The unique CIVIC aspect of this project is to leverage existing collaborations with a CERT organization to assess the feasibility. The long-term vision is to develop a sustainable, replicable, and empirically informed framework for integrating CERT volunteers into the automated processing of social media data using an AI-based system. The project supports education and diversity by providing research experiences to diverse students, as well as training CERT volunteers in social media and human-AI teaming. Findings can help emergency managers better train their volunteers who comb through social media using understandings of the built environment to help machines see new patterns in data. Hence, this project supports NSF's mission to promote the progress of science and advance the nation's health, prosperity, and welfare by demonstrating the value of leveraging local CERT volunteers, in partnership with emergency managers, to generate disaster situation awareness. The goal of this planning grant is to analyze existing human-AI teaming disaster data and involve civic partners in focus groups to better understand the attitudes and beliefs of CERT volunteers, emergency managers, key governmental organizations, and non-governmental organizations. This project will develop deep knowledge of digital volunteer teams, how they work, how to motivate them, and how to have them support the objectives of emergency managers. Thus, we advance theory around volunteer teaming in the technology space and human-in-the-loop protocols. This project provides meaningful ways for more citizens to participate in disaster planning and response, and develops a training curriculum for CERT volunteers who work with social media data in an effort to build sustainable volunteer efforts.This project is in response to Track B - CIVIC Innovation Challenge - Resilience to Natural Disasters a collaboration with NSF and the Department of Homeland Security.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.

应急管理人员需要访问正确的数据来有效、高效地规划和应对灾害。社交媒体提供了与灾害管理越来越相关的数据源，但应急响应组织通常缺乏大规模监控和挖掘社交媒体数据的能力。一种补救措施是将标记相关信息的人类志愿者与计算机配对，以训练和更新人工智能 (AI) 系统，以实现可扩展的监控。在此过程中让当地志愿者参与非常重要，因为他们具有识别本地相关图像、文本的独特能力。，以及反映他们社区的对话。我们目前还没有系统地将这些人类志愿者/人工智能系统与应急管理组织配对的机制，因此，该项目研究的根本问题是利用人工智能与社区应急响应小组（CERT）当地成员的优势的可行性。该项目的独特之处在于利用与 CERT 组织的现有合作来评估可行性。将 CERT 志愿者整合到自动化中该项目通过为不同的学生提供研究经验以及在社交媒体和人类人工智能团队方面培训 CERT 志愿者来支持教育和多样性。研究结果可以帮助应急管理人员更好地培训他们的志愿者。他们利用对建筑环境的理解来梳理社交媒体，帮助机器看到数据的新模式。因此，该项目支持 NSF 的使命，即通过展示利用当地的价值来促进科学进步并促进国家的健康、繁荣和福利。 CERT 志愿者与这项规划拨款的目标是分析现有的人类与人工智能协作灾难数据，并让民间合作伙伴参与焦点小组，以更好地了解 CERT 志愿者、应急管理人员、主要政府组织的态度和信念。该项目将深入了解数字志愿者团队、他们如何工作、如何激励他们以及如何让他们支持应急管理人员的目标，从而推进技术领域志愿者团队的理论。该项目提供了人机交互协议。为更多公民参与灾难规划和响应提供有意义的方式，并为使用社交媒体数据的 CERT 志愿者开发培训课程，以努力建立可持续的志愿者工作。该项目是为了响应 Track B - CIVIC 创新挑战 - 复原力该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Human-AI teaming for COVID-19 response: A practice & research collaboration case study

人类与人工智能合作应对 COVID-19：一种实践

DOI：
发表时间：
2022-05
期刊：
Proceedings of the 19th International ISCRAM Conference
影响因子：
0
作者：
Hughes, A.;Stephens, K. K.;Peterson, S.;Purohit, H.;Harris, A. G.;Senarath, Y.;Jarvis, S. A.;Montagnolo, C. E.;Nader, K.
通讯作者：
Nader, K.

Implementation of a multidisciplinary COVID-19 social media capability in uncertain times.

在不确定时期实施多学科的 COVID-19 社交媒体功能。