Addressing Procedural and Tooling Challenges in Juvenile Justice: Towards Responsible and Human-Centered Design

Paper Title

Addressing Procedural and Tooling Challenges in Juvenile Justice: Towards Responsible and Human-Centered Design

Publication Info

• Topic area: Socio-technical challenges and design opportunities in juvenile justice systems.
• Keywords: Juvenile justice, case management, systemic inequities, human-centered design, responsible AI, Critical Race Theory, inter-agency coordination, trauma-informed care, workforce challenges, design fiction.

Background and Problem

• Problem / challenge: The Department of Juvenile Justice (DJJ) faces systemic inefficiencies, fragmented documentation, and workforce shortages, which lead to misdiagnoses, unsafe placements, and missed opportunities for early intervention and recognizing youth progress. Existing tools and processes fail to meet the unique needs of DJJ staff and youth.
• Significance: These challenges directly impact the care and rehabilitation of youth, perpetuating systemic inequities and increasing recidivism rates. Addressing these issues is critical to improving outcomes for vulnerable populations.
• Motivation and related work: Prior advancements in AI for government services (e.g., Child Welfare System, Department of Justice) have shown potential for improving decision-making and resource allocation but have also highlighted risks such as bias, lack of transparency, and poor integration. This study builds on these lessons to explore the specific needs of DJJ staff and youth.

Solution

• Proposed approach: A Human-Centered Responsible AI (HCR-AI) framework is proposed to guide the design of future tools that address systemic challenges in DJJ workflows. The study uses design fiction memos to explore speculative solutions.
• Novelty:
  1. Extends well-documented workforce challenges to the unexplored context of DJJ.
  2. Applies Critical Race Theory (CRT) to analyze systemic inequities in juvenile justice.
  3. Proposes speculative AI-enabled tools tailored to DJJ needs, emphasizing interpretability, contextual flexibility, and emotional sustainability.
  4. Highlights the importance of grounding technology design in the lived experiences of DJJ staff and youth.
• Procedure and key techniques:
  • Conducted 15 semi-structured interviews with DJJ employees and subcontractors.
  • Analyzed data using reflexive thematic analysis informed by CRT.
  • Developed speculative design fiction memos to envision AI-enabled tools addressing identified challenges.

Results

• Concrete findings:
  • Systemic inefficiencies, fragmented documentation, and understaffing lead to misdiagnoses, delayed interventions, and compromised care for youth.
  • High turnover rates and insufficient training exacerbate these challenges.
  • Current tools like JJMS are disjointed and inefficient, requiring manual workarounds.
• Advantage over baselines:
  • Proposed AI tools aim to address gaps in pattern recognition, documentation, and inter-agency coordination, offering tailored insights and reducing administrative burdens.
• Experiments / evaluation:
  • Interviews focused on understanding DJJ workflows, tooling challenges, and staff perspectives on AI.
  • Design fiction memos were used to explore speculative solutions but were not co-designed or tested with participants.
• Limitations and future work:
  • The study does not provide tested solutions but speculative directions.
  • Future work should involve co-design with DJJ staff and youth to refine and validate proposed tools.
  • Further research is needed to address intersectional inequities and ensure AI systems do not perpetuate harm.

Summary

This study identifies systemic inefficiencies, fragmented tools, and workforce challenges in the Department of Juvenile Justice, which hinder equitable and effective care for youth. Using Critical Race Theory and Human-Centered Responsible AI as guiding frameworks, the authors propose speculative AI-enabled tools to address these challenges. Design fictions such as a Trauma-Aware Pattern Insight Tool and an Ongoing Journey Tracker illustrate how AI could support pattern recognition, early intervention, and documentation, while preserving human judgment and addressing systemic inequities. These findings lay the groundwork for future research and co-design efforts to ensure technology in juvenile justice prioritizes equity, dignity, and long-term well-being.