SBIR Phase I: A Stakeholder Management Platform for Environmental Justice

这个小企业创新研究第一阶段项目的更广泛的影响/商业影响是，通过为服务不足的社区提供有效的参与工具，打破环境和社会不公正的多代、多部门级联影响的负面反馈循环。随着联邦、州、县和地区各级政府越来越多地采用环境正义政策，在所有监管和规划阶段就明确和有意义地让服务不足的社区参与进来，趋势正在发生转变。本项目旨在解决围绕识别、建立信任和提升社区组织和服务不足社区的自动化过程的最初挑战，目标是加速实施公平的气候智能型基础设施项目。拟议的创新将帮助各机构扩大社区参与的范围、准确性和效率，与服务不足的社区建立和建立信任，并加速社区参与美国各地的规划和基础设施项目。该项目帮助社区领导人提高他们在各机构中的发言权和知名度，获得不同机构间的及时信息，并获得融资机会。成功实施该项目有可能减轻社区的成本负担，同时也支持项目所在社区的经济赋权。这个小企业创新研究第一阶段项目将展示使用TextAI（使用人工智能（AI）的自然语言处理）和GeoAI（使用人工智能的地理信息系统）执行基于位置的社区组织（cbo）利益相关者发现的可行性。这一目标带来了技术挑战：非结构化数据的高度变化；手工标注的质量；属性的复杂性和多样性；消除位置识别和社会挑战的歧义。利益群体对政府和技术的信任度较低，需要透明的数据共享和道德规范。关键的创新是将深度技术开发与社区组织和政府的参与性和包容性共同设计相结合的工作流程。如果项目成功，它将为服务不足的社区带来可观的回报。第一个用例是旧金山湾保护和发展委员会，该委员会拥有适当的规模和管辖范围，可以捕获数据类型、利益相关者和用户的变化，包括城市和农村社区高度多样化的人口统计数据，同时也足够小，可以管理其数据。该奖项反映了美国国家科学基金会的法定使命，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。

The broader impact/commercial impact of this Small Business Innovation Research Phase I project is to break the negative feedback loop of multi-generation, multi-sector cascading impacts of environmental and social injustices by providing effective tools for engagement of underserved communities. The tide is turning as Environmental Justice policies are increasingly being adopted by governments at the federal, state, county, and regional levels - to explicitly and meaningfully engage underserved communities early and often in all regulatory and planning phases. This project addresses the initial challenges around automating the process of identifying, building trust with, and elevating community-based organizations and underserved communities with the goal of accelerating the implementation of equitable climate-smart infrastructure projects. The proposed innovation will help agencies scale up their reach, accuracy, and efficiency of community engagement, establish and build trust with underserved communities, and accelerate community participation in planning and infrastructure projects throughout the United States. The project helps community leaders raise their voice and visibility with agencies, gain access to timely information across different agencies, and gain access to funding opportunities. Successfully implementing this project has the potential to reduce cost burdens on communities, while also supporting economic empowerment in communities where the project is deployed. This Small Business Innovation Research Phase I project will demonstrate feasibility of using TextAI (Natural Language Processing using Artificial Intelligence (AI)) and GeoAI (Geographic Information Systems using AI) to perform location-based stakeholder discovery of Community Based Organizations (CBOs). This goal poses technical challenges: high variation in unstructured data; quality of manual annotations; complexity and diversity of attributes; and disambiguation of location identification and social challenges. The communities of interest have low trust in the government and technology and need transparent data sharing and ethics. The key innovation is a workflow that combines deep technology development with participatory and inclusive co-design with community-based organizations and government. If the project succeeds, it will have substantial payback for underserved communities. The first use case is with the San Francisco Bay Conservation and Development Commission, which has the right size and scope of jurisdiction to capture variations in data type, stakeholders, and users - and includes a highly diverse set of demographics across urban and rural communities - while also being small enough to manage its data.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.