CAREER: An Integrated Trustworthy AI Research and Education Framework for Modeling Human Behavior in Climate Disasters

职业生涯：用于模拟气候灾害中人类行为的综合可信人工智能研究和教育框架

• 批准号: 2338959
• 负责人: Xilei Zhao
• 金额: $ 54.92万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2029-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2338959&HistoricalAwards=false
• 关键词: CAREER; Integrated; Trustworthy; AI; Research

Increase in frequency and severity of weather and climate disasters has resulted in greater harm to human lives, civil infrastructures, and the economy. An essential step toward building disaster resilience requires deep understanding and robust modeling of human behaviors before, during, and after catastrophic events. This Faculty Early Career Development (CAREER) project supports research on trustworthy Artificial Intelligence (AI) methodologies to transform behavioral modeling in weather and climate disasters and advances STEM education and emergency management practices. Such theory-informed, high-resolution models are explainable, and bias in them is minimized in support of time- and safety-critical decisions. The project contributes to training of the next-generation scientists and engineers to build and utilize cutting-edge AI tools for disaster management. Research on harnessing AI to enhance human behavioral modeling in disasters is emerging but still in its infancy. Notably, many of the current models function as a black box and have not thoroughly considered critical issues such as trustworthiness, bias, and fairness. This project fills the knowledge gap by developing an integrated trustworthy AI research and education framework. Five main tasks are pursued: 1) Coupling fundamental theories with data-driven AI approaches to improve the prediction of human behaviors in weather and climate disasters; 2) characterizing fairness issues present in AI-based behavioral models, and reducing inherent bias and inequity; 3) interpreting model inputs and outputs to gain unique insights and advance theories; 4) transferring research outcomes into high school and undergraduate engineering curricula; and 5) providing training opportunities to emergency managers and transportation professionals to enhance their technological competency. Collectively, this CAREEER project has the potential to yield significant improvement to emergency management, social equity, and community resilience.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.

天气和气候灾难的频率和严重程度的增加导致对人类生活，民用基础设施和经济的损害更大。迈向建立灾难恢复能力的重要一步需要对灾难性事件发生之前，期间和之后的人类行为进行深刻的理解和强大的建模。该教师早期职业发展（职业）项目支持可信赖的人工智能研究（AI）方法，以改变天气和气候灾难中的行为建模，并进步STEM教育和紧急管理实践。这种知觉的高分辨率模型是可以解释的，并且在支持时间和安全关键决策中将其偏见最小化。该项目有助于培训下一代科学家和工程师，以建立和利用尖端的AI工具进行灾难管理。关于利用AI增强灾难中人类行为建模的研究正在出现，但仍处于起步阶段。值得注意的是，许多当前模型充当黑匣子，并且没有完全考虑到关键问题，例如可信赖，偏见和公平。该项目通过开发一个综合值得信赖的AI研究和教育框架来填补知识差距。追求五个主要任务：1）将基本理论与数据驱动的AI方法耦合，以改善天气和气候灾难中人类行为的预测； 2）表征基于AI的行为模型中存在的公平问题，并减少固有的偏见和不平等； 3）解释模型输入和输出以获得独特的见解和进步理论； 4）将研究成果转移到高中和本科工程课程中； 5）为应急管理人员和运输专业人员提供培训机会，以增强其技术能力。总的来说，该护理人员项目有可能对紧急管理，社会公平和社区韧性产生重大改进。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准来评估值得支持的。