CAREER: Community Organizing for Datafied Worlds

该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追求基层领导的项目，并影响数据密集型技术的更广泛使用，特别是当这些使用涉及提供公共服务时。该项目的每一个方面都深深地融入了互惠的精神，这种精神承认少数群体社区本身已经拥有重要的专门知识，学术知识应该成为基于社区的解决方案的资产。该项目承诺在追求这一精神的过程中至少取得五项成果：（1）有意义地将少数群体社区纳入关于数据行动主义和数据密集型技术社会后果的研究设计、实施和交流;（2）将经常被边缘化的声音纳入人机交互和社会计算研究，特别是黑人妇女和有色人种青年;（3）将来自服务不足背景的学生纳入研究和教学;（4）促进有色人种工人阶级社区数据素养的外展活动;（5）为文化知情的K-12数据科学教育做出贡献，在服务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）研究社区组织者的数据实践与技术，（2）与社区组织者作为合作伙伴共同设计，（3）构建一个平台，以支持社区组织者的学术研究，以及（4）推广，以促进有色人种工人阶级社区的数据素养。该项目采用定性方法，通过询问社区组织者如何解决数据密集型技术的危害（例如，人工智能，机器学习和预测分析）已经部署在他们的社区中。该项目还包括一系列以就业和结构性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少数群体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适当和有害负担的地方进行文化知情的数据扫盲。该奖项反映了NSF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。

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.