Identifying Potential Impacts of Artificial Intelligence in the State Court Workplace Using a Multi-team Systems Approach

State courts hear over 95 percent of all legal matters in the U.S., and they play an important role in the lives of individuals and communities. Like many organizations in the private sector, state courts have begun to look closely at the potential for integrating AI technologies into their operations. There are many ways in which AI might improve court operations and enhance the courts’ services to the public, including improving caseflow management, interfacing with court users and helping them navigate court systems, or aiding substantive legal decision making to improve case outcomes. However, the stakes involved in implementing new AI technologies in this sector are also high; courts have duties to safeguard the constitutional rights of court users, and the decisions they make can be life-altering. These high stakes make it vital that courts are involved in the selection and development of these technologies from the ground up. This project aims to contribute to the science of organizations by examining the effects of organizational and team attributes on AI integration potential. It also generates new knowledge and resources for the state courts: an interactive tool that visualizes multi-layered network models of the state court workforce and reports and resources that provide actionable guidance related to AI implementation in the courts. In the long run, facilitating the successful integration of AI into the state courts through organizational research has the potential to increase access to the courts for court users, make court workforces more diverse and employment outcomes more equitable, increase efficiency in case processing, and bolster public trust and confidence in the courts. This three-year project brings researchers and court professionals together to 1) map the state court workforce using a multiteam systems approach and 2) identify points in the court workflow where AI integration might be more beneficial or detrimental to the courts’ organizational goals. First, the project team uses an extensive workforce survey and social network analysis to map the court workforce and the roles of individuals and teams within it. The researchers examine the structure of the workforce; interrelations among different workers, tasks, activities, and skills; impacts of individual workers on the caseflow process; and workers’ perspectives on the potential roles of AI in their work. Second, the project team uses these network models to predict potential impacts of AI at different points in the caseflow process. The researchers also identify AI applications with the greatest potential to enhance the effectiveness and efficiency of these job-holders, promote job satisfaction and well-being, and align with the goals and purposes of the state courts in society. 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.