NEW TEAM: Law, Data & Design Lab

2024 ~ Present | National Science Foundation Convergence Accelerator and Proto-OKN programs; potential additional future NSF and foundation funds.

Goals

The Law, Data & Design Lab works to increase fairness, efficiency, transparency, and access to justice in the civil and criminal legal systems in the United States and around the world. We use methods from computer and data science (e.g., natural language processing, machine and deep learning), operations management (e.g., process mining, simulation), public policy (e.g., program evaluation, case studies), and design (e.g., human centered design, contextual inquiry, dataviz) to develop innovative approaches to solving justice problems.

Issues Involved or Addressed

The civil and criminal legal systems face a set of complex problems, including inequitable procedures and outcomes, backlogs and delay, and the difficulty of finding and affording quality legal representation, especially for low-income litigants. Better data can offer some solutions, by identifying patterns that suggest bias, or by pinpointing circumstances where cost and delay might be addressed with some intervention. Engagement with the people who are actors in, and are acted upon by, the civil and criminal legal systems is equally important. These include judges and court staff, lawyers, litigants, law enforcement, policymakers, academics, and community members. Leveraging these groups’ knowledge and experience enables better experimentation with and design of solutions. Example projects include: • The SCALES Open Knowledge Network: building an AI-powered data repository that makes federal court records and information freely and publicly available • The Integrated Justice Platform: synthesizing arrest, court, and incarceration records from metro Atlanta and Seattle, with plans to expand nationwide • The Court Congestion Project: analyzing case processing times and modeling the impact of resource changes on court congestion and other justice outcomes • The (In)Credible Evidence Project: exploring how legal rules and societal ideas about data, technology, and credibility shape the evidence that litigants offer, and what is believed, in and outside of court

Methods and Technologies

  • Python programming, especially NLP applications
  • Human-centered design
  • Data visualization
  • Data cleaning and management
  • Operations Management, especially process mining

Academic Majors of Interest

  • BusinessLeadership and Organizational Change
  • BusinessOperations and Supply Chain Management
  • BusinessStrategy and Innovation
  • ComputingAnalytics
  • ComputingComputer Science
  • ComputingHuman-Centered Computing
  • Design
  • Ivan AllenPublic Policy

Preferred Interests and Preparation

Highly motivated and interested in working across disciplines in teams on real-world problems. No prior knowledge of law or the U.S. legal system required, but such knowledge or experience is a plus. Must be organized, responsible, willing to learn, flexible, and a good communicator with teammates, instructors, and external partners and collaborators.

Meeting Schedule & Location

Time 
11:00-11:50
Meeting Day 
Wednesday

Team Advisors

Charlotte Alexander
  • Scheller College of Business

Partner(s) and Sponsor(s)

National Science Foundation Convergence Accelerator and Proto-OKN programs; potential additional future NSF and foundation funds.