Defending Data proposes a data-driven, systems-based approach to improving public defense in America.
Public defenders represent millions of defendants every year. Yet, public defense remains a largely data-less enterprise, a black box of discretionary decisions disconnected from any systemic analysis about the relationship between defender practices and case outcomes. Defending Data adopts a novel approach to the crisis of public defense. Building off of the successful implementation of system-based approaches in other complex, high-risk industries such as aviation and medicine, Defending Data explains how defenders can develop a data-driven systems approach to public defense.
Defending Data begins by describing the data deficit in public defense and discussing the systemic, technological, and cultural reasons for this data-void. Then, Defending Data explains the systems approach to high-stakes professional practices and explores how public defenders can adapt this approach to the delivery of indigent defense services. Based on this analysis, Defending Data proposes a systems approach to public defense and offers a preliminary typology of the data that such public defenders should collect and analyze. Using concrete examples, Defending Data demonstrates how public defender systems might implement a data-driven systems approach. Defending Data concludes with a call for the indigent defense community to reimagine indigent defense by establishing national standards for defending data.
Southern California Law Review
data analysis, criminal defense, Gideon, indigent defense, evidence-based, big data, systems approach
Pamela Metzger; Andrew Guthrie Ferguson, Defending Data, 88 S. Cal. L. Rev. 1057 (2015)