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

Prairie View A & M University, Prairie View TX

Investigators

Abstract

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.