SCC-IRG Track 2: Diaspora, Agriculture, & AI: Community-based Integration of Smart Technologies into Black Diasporic Agricultural Practices

SCC-IRG 第 2 轨：侨民、农业、

• 批准号: 2310515
• 负责人: Sucheta Ghoshal
• 金额: $ 166万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-15 至 2026-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2310515&HistoricalAwards=false
• 关键词: SCC; IRG; Track; Diaspora; Agriculture

Black diasporic farming communities are important sites of sustainable food production for millions of people in the US and worldwide. As tight-knit agricultural collectives, they generate food throughout cities, promote diasporic values of ecological well-being, resource conservation, and interdependence, and foster the possibility of social and political transformation for black, indigenous, racialized and marginalized groups. While advancements in food security, nutrition, and environmental health have the potential to feed nearly twice as many people per year, particularly among historically marginalized groups, black diasporic urban farming communities face several hurdles to efficiency that remain largely under-addressed. Activities such as risk management, soil health monitoring, and crop harvesting rely on repeated, time-consuming work that is challenging to support on limited budgets, resources, and labor. The field of artificial intelligence (AI) promises solutions to many of these challenges, making the case for an emerging market around AI-driven agricultural technologies. This project aims to (1) advance understanding of sociotechnical ecosystems involving AI to support diasporic urban farming; (2) collaboratively develop AI-based technologies that better integrates and sustains technological gains with diasporic knowledge, and (3) systematically assess the impact of AI-based farming technologies on diasporic communities and industrial partners. In particular, our research seeks to advance the field of smart agriculture for diasporic urban farming communities along three urgent axes: (1) Labor: Addressing labor needs, decreasing bias within weeding, and ensuring access to affordable services for farmers who need them; (2) Ecosystem: Advancing care for a farm’s ecological conditions by supporting synergistic relationships with the land and surrounding organisms, training novice farmers, and monitoring greenhouse conditions; (3) Health: Innovating mechanisms for healthy soil conditions, reducing toxicity, and increasing the quality and quantity of nutrients. This work unfolds across three phases. Phase 1 begins with an ethnographic case study involving participant observation of urban agricultural practices and semi-structured interviews with partner organizations and identified stakeholders. Phase 2 complements this empirical work with an evaluation and design study that identifies sociotechnical solutions for agricultural decision-making informed by black diasporic needs. Phase 3 involves technical implementation that mindfully integrates black diasporic knowledge with AI-based technologies towards a smart and connected diasporic farming infrastructure. This work relies on our interdisciplinary team’s close collaboration with three farming organizations, three industry partners, and sustained partnerships across wider diasporic farming networks, and oversight from experts in AI, HCI, critical geography, urban studies, and community-based inquiry.This project is partially funded by the Advancing Informal STEM Learning (AISL) program, which is committed to funding research and practice with continued focus on investigating a range of informal STEM learning (ISL) experiences and environments that make lifelong learning a reality.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.

黑人散居农业社区是美国和全世界数百万人可持续粮食生产的重要场所。作为紧密结合的农业集体，他们在整个城市生产粮食，促进生态福祉，资源保护和相互依存的散居价值观，并促进黑人，土著，种族化和边缘化群体的社会和政治转型的可能性。虽然粮食安全、营养和环境卫生方面的进步有可能每年为近两倍的人口提供食物，特别是在历史上被边缘化的群体中，但散居在城市的黑人农业社区在提高效率方面面临着一些障碍，这些障碍在很大程度上仍未得到解决。风险管理、土壤健康监测和作物收获等活动依赖于重复、耗时的工作，在有限的预算、资源和劳动力的支持下，这些工作具有挑战性。人工智能（AI）领域有望解决其中许多挑战，为围绕人工智能驱动的农业技术的新兴市场提供了理由。该项目旨在(1)促进对涉及人工智能的社会技术生态系统的理解，以支持散居的城市农业；(2)协同开发基于人工智能的技术，更好地整合和维持技术成果与流散知识；(3)系统评估基于人工智能的农业技术对流散社区和工业合作伙伴的影响。特别是，我们的研究旨在沿着三个紧迫的轴推进散居城市农业社区的智能农业领域：(1)劳动力：解决劳动力需求，减少除草中的偏见，并确保有需要的农民获得负担得起的服务；(2)生态系统：通过支持与土地和周围生物的协同关系、培训新手农民和监测温室条件，促进对农场生态条件的关注；(3)健康：创新土壤健康机制，降低毒性，提高养分的质量和数量。这项工作分三个阶段展开。第一阶段以人种学案例研究开始，包括对城市农业实践的参与者观察，以及与合作伙伴组织和确定的利益相关者的半结构化访谈。第二阶段通过评估和设计研究补充了这一实证工作，该研究确定了根据散居黑人需求制定农业决策的社会技术解决方案。第三阶段涉及技术实施，将黑人散居知识与基于人工智能的技术相结合，以实现智能和互联的散居农业基础设施。这项工作依赖于我们的跨学科团队与三个农业组织、三个行业合作伙伴的密切合作，以及更广泛的散居农业网络的持续伙伴关系，以及人工智能、HCI、关键地理、城市研究和社区调查专家的监督。该项目部分由推进非正式STEM学习（AISL）计划资助，该计划致力于资助研究和实践，并继续关注调查一系列非正式STEM学习（ISL）经验和环境，使终身学习成为现实。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。