CAREER: Community Organizing for Datafied Worlds

本项目描述了有色人种工人阶级社区的专业社区组织者如何使用数据来开展基层主导的项目，并影响数据密集型技术的更广泛使用，特别是因为这种使用关系到公共服务的提供。该项目的每一个方面都深受互惠精神的影响，承认少数群体社区本身已经拥有重要的专门知识，学术知识应该是以社区为基础的解决方案的资产。该项目承诺在追求这一风气方面至少取得五项成果：(1)使少数群体社区有意义地参与关于数据激进主义和数据密集型技术的社会后果的研究的设计、实施和交流；(2)在人机交互和社会计算研究中纳入经常被边缘化的声音，特别是黑人妇女和有色人种青年；(3)在研究和教学中纳入服务不足背景的学生；(4)在有色人种工人阶级社区中促进数据扫盲的外联活动；以及(5)促进了解文化知识的K-12数据科学教育，在服务于有色人种工人阶级社区的学校进行试点和测试。该项目分为四个部分：(1)研究从事技术的社区组织者的数据实践；(2)与社区组织者作为合作伙伴共同设计；(3)建立一个平台，支持对社区组织者的学术研究；(4)推广有色人种工人阶级社区的数据素养。该项目部署定性方法，通过询问社区组织者如何应对已部署在其社区中的数据密集型技术(例如，人工智能、机器学习和预测分析)的危害，来极大地扩展对数据实践和数据通信的持续研究。该项目还包括一系列以数据通信和结构不平等为重点的讲习班。此外，正在进行的参与式设计的结果将形成一个社区行动案例研究平台，这是一个帮助学术研究人员更公平地与小规模社区接触并了解数据密集型技术造成的持续危害的工具。最后，教育和推广项目将有助于在数据密集型技术产生不必要和有害负担的地点进行文化信息数据扫盲。这一奖项反映了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。

This project describes how professional community organizers in working-class communities of color use data to pursue grassroots-led projects and to influence broader uses of data-intensive technologies, particularly as such uses concern provision of public services. Every aspect of this project is deeply informed with an ethos of reciprocity, one that recognizes that minority communities themselves already have important expertise and that academic knowledge should be an asset to community-based solutions. This project promises at least five outcomes in pursuit of this ethos: (1) meaningful incorporation of minority communities in research design, implementation, and communication of research on data activism and social consequence of data-intensive technologies; (2) incorporation of frequently marginalized voices in human-computer interaction and social computing research, particularly Black women and youth of color; (3) inclusion of students from underserved backgrounds in research and teaching; (4) outreach activities to promote data literacy in working class communities of color; and (5) contributions toward culturally informed K-12 data science education, piloted and tested in schools that serve working-class communities of color. The project is organized into four parts: (1) research on data practices of community organizers engaged with technology, (2) co-design with community organizers as partners, (3) construction of a platform to support academic research on community organizers, and (4) outreach to promote data literacy in working class communities of color. This project deploys qualitative methods to greatly expand ongoing research into data practices and datafication by asking how community organizers address the harms of data-intensive technologies (e.g., artificial intelligence, machine learning, and predictive analytics) already deployed in their communities. This project also includes a series of workshops focused on datafication and structural inequality. In addition, the results of ongoing participatory design will shape a community action case study platform, a tool to help academic researchers more equitably engage with minoritized communities and learn about ongoing harms posed by data-intensive technologies. Finally, education and outreach projects will contribute to culturally-informed data literacy in sites where data-intensive technologies have produced undue and harmful burdens.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.