The Use of Big Data in Thailand’s Justice System

Abstract

This study aims to explore the primary conditions, existing problems, and solutions of large-scale database management (Big Data) for preventing and controlling recidivism. This study was qualitative research with a documentary research method. The three main problems in this study were collecting primary data from government agencies and collecting secondary data from significant research databases using a 5-step content analysis technique to obtain accurate and complete information according to the research purpose and significant findings. The infrastructure of information systems in each justice agency has different standards. Relevant justice agencies have different definitions and counts of recidivism. The screening tools' ability to assess the recidivism risk among prisoners remains limited. The results showed that a data exchange center should be established to connect the judiciary in a single way and verify the accuracy of the data. The definition and counting of recidivism data should be standardized in each justice agency to enable accurate data analysis. The screening tools used to figure out how likely it is that a prisoner will return to jail should be made better by using clearer language and ensuring the questions are about the right thing.