Strategies for Responsible Data Sharing between Administrative Agencies – A Presentation to the Arnold Foundation Data Driven Criminal Justice Projects Coaching Program

The goal of the Data Driven Criminal Justice Projects Coaching Program, supported by a grant from the Laura and John Arnold Foundation and organized by The GovLab, is to support the work of public entrepreneurs trying to improve people’s lives. The twenty teams and individuals participating are among those who are fighting to improve the criminal justice system and who have asked for help integrating new technology into hidebound bureaucracies or developing approaches for sharing data responsibly.

Starting the second week of June, the GovLab, an action research institute based at New York University, has been providing skill-based coaching and expert mentoring to practitioners who share a common desire to make greater use of data to understand past performance, improve day-to-day operations, and develop innovative enhancements to the operations of the criminal justice system.  We are supporting work at the local level, for example, to build a better recidivism risk profile, develop a process for matching the supply and demand of crisis psychiatric beds to reduce the number of mentally ill people going to jail, and identifying how many juveniles are sent to juvenile hall versus those who are diverted to other programs.

During the third online group session of the coaching program on July 13, we brought in experts on data sharing between administrative agencies to help those working on projects designed to enable the sharing of information between criminal justice and mental health agencies, in particular. More details about the session here.

The first of those presentations was by Stefaan Verhulst, Co-Founder and Chief Research and Development Officer at the GovLab, who spoke about frameworks for responsible data sharing :

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Overview of the presentation: In this presentation, Stefaan focused on how to develop data driven criminal justice initiatives in a responsible manner. There are substantial risks across the data life cycle –collection, analysis and use of data– that, if not addressed or mitigated, may harm the intended beneficiaries (in terms of harmful disclosure of sensitive information or negative profiling) or those part of the initiative (in terms of reputation, liability and otherwise). By applying a four step process organizations can establish responsible data practices that are embedded from the outset of a project.

Please find the slide-deck of presentation here.