EFFICACY OF ARTIFICIAL INTELLIGENCE (AI) THEORY AND EDUCATIONAL/VOCATIONAL TRAINING AT REDUCING RECIDIVISM IN SOUTH-WEST NIGERIA

Abstract

Recidivism which is a situation whereby individuals previously convicted of crime tend to return to crime again has been attributed to a lack of appropriate skills, interest and market demand for recidivists. This study therefore examines the efficacy of Artificial Intelligence (AI) theory in designing personalized educational/vocational training that matches the skills of inmates with market demand for the reduction of recidivism. The cross-sectional survey employed a descriptive research design and purposive sampling method. The study sample size is 89 based on a multistage sampling method in a correctional centre in South West, Nigeria (Oyo, Ondo and Osun State). Structured questionnaires were used to harvest information on recidivists and utilization of AI in the design of educational/vocational programmes for recidivists. Data generated were analyzed using Artificial Neutral Network and regression analysis. The study shows inappropriate educational/vocational programmes for recidivists that does not match inmates’ skills and interest as some of the causative factors of recidivism in South West Nigeria. The study findings have theoretical and advocacy implications for policy makers and educators within the Nigerian correctional facilities system by emphasizing the need to adopt AI theory for predicting recidivists’ behavior change in response to educational/vocational training. The study concluded that the adoption of AI theory in the design of appropriate training that matches skills, interest and market demand would facilitate the reduction of recidivism in the society. The study recommended that government, policymakers and educators need to adopt AI theory in designing appropriate personalized educational/vocational training that matches inmates’ skills and interests with market driven demands as strategy for reducing recidivism in the society.