CAP: Semi-supervised Fairness-Enhanced Knowledge Graph Construction on Social Media for AI-Enhanced Juvenile Justice

该项目是一个扩大人工智能能力建设试点(CAP)，重点是通过利用人工智能技术和社交媒体数据，在草原景观农工大学建立和发展与人工智能相关的活动，以显著加强暴力预防和为青少年伸张正义。社交媒体是煽动肢体冲突的帮派青年以及分享暴力和帮派冲突信息的社区成员的主要信息来源。通过草原景观农工大学工程学院和少年司法学院的合作，将使用从社交媒体提取的数据构建公平增强的知识图谱。这些知识图(KG)是用于表示智能系统用于解决复杂问题的事实的结构。幼儿园将去偏见，并用来揭示青少年暴力循环的机制、后果和地方知识。该项目预计将显著增强草原景观农工大学(HBCU)的人工智能研究和教学能力。该项目将促进公平并加强暴力预防，促进自然语言处理、计算机视觉、机器学习和值得信赖的人工智能领域中受使用启发的人工智能的研究。在教育方面，计划的活动不仅将使非裔美国学生获得重要的尖端跨学科技能，还将显著扩展COE和COJJ学生的职业道路。加强公平的知识图谱构建过程涉及若干任务，包括：(1)加强社交媒体平台上与司法有关的数据的公正性；(2)半监督的FKG构建；(3)全面的FKG质量评估和工具开发。将使用基于人在环的群体学习方法将用户反馈整合到学习中，以促进假新闻检测。在构建知识图的过程中，将使用去偏向技术来提高公平性。该项目将改革两所学院现有课程的内容，为学生提供指导，并为与司法应用相关的人工智能比赛提供培训。与NVIDIA深度学习研究所等外部组织合作，将开发用于人工智能培训的教材包，此外，还将与社区、HBCU和其他组织进行接触。该项目由历史黑人学院和大学本科项目(HBCU-UP)共同资助，该项目提供奖项，以加强HBCU的STEM本科教育和研究。扩展人工智能计划支持少数族裔服务机构的人工智能驱动的教育和劳动力发展、基础设施和研究，以加强和多样化美国的研究和教育途径，并在STEM职业生涯中为历史上被边缘化的社区提供新的机会。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 project is an ExpandAI Capacity building pilot (CAP), which focuses on establishing and growing AI related activities at Prairie View A & M University by utilizing AI technology and social media data for significant enhancement of violence prevention and delivery of justice to juveniles. Social media is a major source of information for gang-associated youth who instigate physical conflicts as well as community members who share information about violence and gang conflicts. Through a collaboration between Prairie View A&M University College of Engineering and College of Juvenile Justice, fairness-enhanced knowledge graphs will be constructed using data extracted from social media. These knowledge graphs (KG) are constructs for the representation of facts used by intelligent systems for the solution of complex problems. KGs will be de-biased and used to uncover mechanisms for, consequences of, and local knowledge about the cycle of youth violence. The project is expected to significantly enhance the AI research and instruction capacity of Prairie View A&M University – an HBCU. The project will promote fairness and enhance violence prevention, catalyzing research in use-inspired AI in the fields of natural language processing, computer vision, machine learning and trustworthy AI. On the educational side, the activities planned will not only enable African American students to acquire important cutting-edge cross-disciplinary skills but also significantly expand the career pathways for both COE and COJJ students. The fairness-enhanced knowledge graph construction process involves several tasks including (i) enhancement of the fairness of justice-related data represented on social media platforms; (ii) semi-supervised FKG construction; and (iii) comprehensive FKG quality assessment and tool development. A human-in-the-loop based swarm learning approach will be used to integrate user feedback into learning to facilitate fake news detection. De-biasing techniques will be employed to enhance fairness during Knowledge Graph construction. The project will revamp elements of existing curricula across both colleges, provide mentoring for students and training for AI competitions related to justice applications. In collaboration with external organizations like NVIDIA Deep Learning Institute, teaching kits for AI training will be developed, furthermore, there will be outreach to the community, HBCU and beyond. This project is co-funded by the Historically Black Colleges and Universities Undergraduate Program (HBCU-UP), which provides awards to strengthen STEM undergraduate education and research at HBCUs. The ExpandAI Program supports AI-powered education and workforce development, infrastructure and research at Minority Serving Institutions to strengthen and diversify U.S. research and education pathways and provide historically marginalized communities with new opportunities in STEM careers.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.