This study examines how systemic inefficiencies in the Department of Juvenile Justice (DJJ) constrain care for youth and burden staff. Through 15 semi-structured interviews with DJJ employees and subcontractors, analyzed using reflexive thematic analysis and informed by Critical Race Theory, we surface breakdowns in inter-agency coordination, case management processes, and fragmented documentation across tools, all exacerbated by workforce shortages. Participants described how these conditions contribute to misdiagnoses, unsafe placements, delayed responses, and missed opportunities to recognize youth progress, envisioning future Artificial Intelligence (AI) tools to mitigate the negative impacts. We situate participants’ cautious hopes for AI within a Human-Centered Responsible AI lens and present researcher-generated design fictions as provocations that imagine advisory tools for pattern detection, trend identification, and documentation support while preserving human judgment. By centering staff experiences and systemic inequities, this work lays the groundwork for the design of future socio-technical interventions in juvenile justice.
ACM CHI Conference on Human Factors in Computing Systems