SBIR Phase II: AI-Integrated Novel Platform to Power Positive Change in Youth and Increase Public Safety

Award ID: 2451784

The broader impact of this SBIR Phase II project lies in advancing an AI-enhanced platform that equips justice-involved youth with essential life skills and fosters positive, lasting change. By integrating state-of-the-art, generative artificial intelligence with evidence-based practices, the project replaces inconsistent interventions with a comprehensive, scalable solution designed to lower programming costs, reduce recidivism and promote public safety. Building on Phase I integration of AI into a positive growth platform and successful implementations in multiple counties, this initiative not only enhances the quality of juvenile justice programming but supports data-driven insights into how generative AI can support behavioral change. This solution provides counties a programming solution to ensure that every arrested youth makes positive change. The commercial potential is vast, with broad application to over 3,143 counties that serve up to 800,000 justice-involved youth annually, offering a financially viable model that mitigates the economic and social costs of repeated offenses. This project will ensure that we leverage breakthroughs in generative AI, advanced technologies, behavioral sciences, and the learning sciences to provide next generation programming and ensure the effectiveness of the juvenile justice system in reducing recidivism, while preparing them to be positive, contributing members of society. It is essential that we ensure arrested youth are held accountable for making the personal changes necessary so that they not only avoid future criminal behaviors and associated costs but also become positive contributing members of society. This SBIR Phase II project is focused on optimizing a next-generation, commercially viable platform to meet critical criminogenic needs and promote positive behavioral change among youth leaving the justice system. Leveraging lessons from Phase I, the project enhances its AI capabilities to develop personalized growth plans, deliver accountable feedback, and create effective transition strategies that prepare youth for successful reintegration into society. Through rigorous quasi-experimental studies and continuous iterations based on stakeholder feedback, the research validates the effectiveness of its behavioral change framework and refines the come-alongside service model. The anticipated outcomes include measurable reductions in recidivism, improved life success for at-risk youth, and a transformative impact on the juvenile justice systemwith potential applications extending into mental health and education. This initiative represents a forward-thinking, impactful investment in a scalable solution that ensures arrested youth are supported in making critical personal changes, ultimately enhancing public safety and fostering stronger communities. 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.

NSF Program Director: Lindsay Portnoy