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，通过提供有效的工具让服务不足的社区参与进来，打破环境和社会不公正的多代、多部门连锁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，趋势正在发生转变--在所有监管和规划阶段，尽早明确和有意义地让服务不足的社区参与进来。该项目解决了围绕自动识别、与基于社区的组织和未得到充分服务的社区建立信任和提升过程的初始挑战，目标是加速实施公平的气候智能基础设施项目。拟议的创新将帮助机构扩大其社区参与的范围、准确性和效率，与服务不足的社区建立和建立信任，并加快全美社区对规划和基础设施项目的参与。该项目帮助社区领导人提高他们在机构中的发言权和知名度，获得不同机构的及时信息，并获得资金机会。成功实施这一项目有可能减少社区的成本负担，同时也支持部署该项目的社区的经济赋权。这个小型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AI的地理信息系统)来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多样性；人工注释的质量；属性的复杂性和多样性；以及位置识别和社会挑战的消除歧义。利益集团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。关键的创新是一种将深度技术开发与参与性和包容性的共同设计与社区组织和政府相结合的工作流程。如果该项目成功，它将为服务不足的社区带来可观的回报。第一个案例是旧金山湾保护和发展委员会，该委员会拥有合适的规模和管辖范围，可以捕捉数据类型、利益相关者和用户的变化--包括城市和农村社区的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。

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.