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                  - Home
                  - Grants                      - Project Grants
                    - Technical Assistance Grants
                    - Curriculum Adaptation & Training Grant
                    - Strategic Initiatives Grants
                    - Education Support Program
                    - Funding Toolkit 
                  - News
                  - Grantee Spotlights
                  - Priority Investment Areas                      - Court Pandemic Response and Recovery Grant Program 
                  - Grant Management
                  - About SJI                      - Board of Directors
                    - Executive Director
                    - Past Members
                    - SJI Budget 

### Supporting the Nation's Judicial System & the Public it Serves

#### 					NEWS				

## Natural Language Programming

Natural Language Programming (NLP) is a field of computer science that employs predictive analytics and machine learning with a focus on the interaction between computers and both written and spoken language.  Over the past decade, courts have successfully employed NLP techniques for routine case management tasks such as redaction, data extraction, document classification, and automated data population into databases.  With generous funding from the State Justice Institute, the National Center for State Courts (NCSC) explored the feasibility of NLP to support civil case management.  The project focused on two stages of civil case management — assigning cases at filing to an appropriate case processing track and reviewing case filings to ensure that fundamental guarantees of procedural due process are satisfied before entering final judgment.  The Conference of Chief Justices and the Conference of State Court Administrators identified both stages as critical to effective civil case management in their recommendations for the Civil Justice Initiative. 

The studies employed NLP techniques for data extraction, relational matching, and document classification, comparing its performance with the same tasks performed by trained staff.  On data extraction tests, NLP performed at 90% or higher on most data elements needed for case triage, and likely would have performed even better with additional human direction during the machine learning phase of the study.  It was less successful on the document classification test, but largely due to poor image quality on the documents themselves rather than inability to accurately extract the necessary data for analysis.  Based on the findings, NCSC emphasized the need for adequate human involvement in the machine learning phase to ensure consistent and accurate performance as well as high quality data on which to begin learning.  In addition to the final report, the NCSC developed instructional videos on NLP and other artificial intelligence technologies, strategies for implementing these technologies, and a resource guide, all of which are available at https://www.ncsc.org/cji.

#### LATEST NEWS & ANNOUNCEMENTS

                  -  Sixteen State Courts Participate in Groundbreaking Workshop for Racial Justice Education  Read More**   
                  -  New Resource: The Rural Justice Collaborative Digest for June 2024  Read More**   
                  -  SJI Board Awards FY 2024 Third Quarter Grants  Read More**   
                  -  SJI Executive Director, Jonathan Mattiello, Congressional Briefing Panelist on Capitol Hill  Read More**   

#### CONTACT US

          contact@sji.gov
                       Tel: 703.660.4979

#### HEADQUARTERS

                       State Justice Institute
                       12700 Fair Lakes Circle, Suite 340
                       Fairfax, VA 22033         

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