SCC-PG: Smart Technologies and Community Engagement to Address Data Gaps in Birth Outcomes Reporting

这项为期一年的计划拨款由亚利桑那州立大学、伍斯特理工学院和出生工作者颜色集体(BCC)合作，调查加利福尼亚州长滩的一个生育工作者社区的技术使用情况，以想象智能技术如何改善通过洛杉矶妈妈和婴儿(LAMB)调查收集的数据的收集、质量和准确性。这项调查对解决不同洛杉矶社区面临的围产期问题的战略产生了至关重要的影响。尽管羔羊调查数据在制定公共卫生政策和资源分配方面很重要，但该调查目前在公布调查结果方面滞后了两年多，未能收集弱势群体的数据。需要解决的重要研究问题包括：密件抄送达拉斯的日常技术实践是什么？更多样化的从业人员群体如何有助于产生一个更少偏见和更安全的数据收集系统？该计划拨款中提出的问题旨在1)记录了解社区合作伙伴需求并将其整合到智能技术设计中的过程，2)增加关于在综合学习中减轻算法偏差的知识，3)提高弱势群体中数据收集的安全性和可信度。该项目涉及重要的社会和技术层面，以审查改善生育结果和弱势社区后续护理的方法。该小组采取多学科方法来解决关键问题，包括设计和评估基于社区的研究方法、集成的人和计算机系统，同时还考虑到人工智能和基于过程的系统的道德规范。拟议的规划活动包括与BCC DULA一起举办三次研讨会，以建立对研究人员的信任和研究过程的完整性；检查BCC已在使用的技术系统和基础设施并确定技术行为；以及引入相关智能技术，共同了解DULA的现场专业知识如何将数据收集差异降至最低。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。

This one-year planning grant, a collaboration between Arizona State University, Worcester Polytechnic Institute, and the Birthworkers of Color Collective (BCC), investigates technology usage in a community of birthworkers in Long Beach, CA to imagine how smart technologies could improve the collection, quality and accuracy of data that is collected through the Los Angeles Mommy and Baby (LAMB) survey. This survey critically influences strategies addressing perinatal issues faced by different LA communities. Despite the importance of LAMB survey data in shaping public health policy and the allocation of resources, the survey currently lags more than two years in publishing survey results, and fails to capture data from vulnerable populations. Important research questions to be addressed include: What are BCC doulas’ everyday technology practices? and How can a more diverse practitioner population contribute to the production of a less biased and more secure data collection system? The questions asked in this planning grant aim to 1) document the process of understanding and integrating community partner needs into smart technology design, 2) increase knowledge about mitigating algorithmic biases in synthetic learning and 3) improve the security and trustworthiness of data collection in vulnerable populations. This project addresses important social and technical dimensions to examine approaches for improving birth outcomes and follow-on care for vulnerable communities. The team takes a multidisciplinary approach to address critical issues including design and assessment of community-based research methods, integrated human and computer systems, while also taking into account the ethics of AI and process-based systems. The proposed planning activities include facilitating three workshops with the BCC doulas to develop trust in the researchers and the integrity of the research process; examine technological systems and infrastructures already in use with BCC and determine technology behaviors; and introduce relevant smart technologies to co-develop an understanding of how the doulas’ field expertise can minimize data collection discrepancies.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.