Artificial intelligence-enabled e-services for justice system services delivery in Namibia

Abstract

Background: People living in villages and rural communities across many countries in Africa have limited financial and educational resources to access the services that are provided by the justice system. Thus, making e-services particularly significant. To date, unfortunately, few scholars and researchers have investigated e-services from the justice systems in the context of villages and rural communities in Africa.
Objectives: To fill gaps in the literature and address limitations, we conducted this study to empirically investigate how artificial intelligence (AI) can be used to improve and enhance the e-services and deliverables of the justice system in villages and rural communities.
Method: The theoretical background for the study is the actor-network theory. The core concepts of the theory, such as translation and immutable mobiles, focus on transformation, processes and events involving actors and actor-networks. The case study approach was applied to the Ministry of Justice (MOJ) and a rural community in Namibia, using the qualitative method. Qualitative data were collected from 18 participants through semi-structured interviews.
Results: The findings from the data analysis show that AI can have a positive and significant impact on the justice system e-services and reveal some of the key factors that are fundamentally influencing the process and events.
Conclusion: The research has many theoretical and practical implications for the government, the MOJ, rural communities and academic institutions. Additionally, the findings provide valuable insights, knowledge, and understanding for future research and managerial implications for improving and enhancing the e-services justice delivery in villages and rural Namibian communities.
Contribution: The study highlights and provides some of the benefits, opportunities, strengths and challenges of applying AI to e-services in the justice system in villages and rural communities.