International Journal For Multidisciplinary Research

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

Artificial Intelligence in Prisoner Rehabilitation: A New Approach to Lowering Recidivism in India

Author(s) Ms. Sukhjeet Kour, Prof. Dr. Mukesh Kumar Garg, Dr. Naresh Lata
Country India
Abstract Prisoner rehabilitation is a debated issue in the criminal justice delivery system. Recidivism among prisoners is a pressing issue that requires immediate attention. Rehabilitation of prisoners can reduce recidivism and facilitate their reintegration into society. In the present era, artificial intelligence (AI) can transform the rehabilitation efforts of prisoners in India. Prisoners face various issues living in society, such as a lack of financial resources, overcrowding, and a lack of rehabilitation programs. The working method of AI can help rehabilitate prisoners, lowering the recidivism rates in India. Psychological testing, vocational training, and individualized rehabilitation programs are the main aspects of prisoner rehabilitation. Artificial intelligence includes various tools, such as language processing, machine learning, and predictive analytics, to help with psychological testing, vocational training, and rehabilitation programs. The authorities can't understand the psychological facts and inmate behavior of prisoners. AI-based learning: the concept of virtual reality can provide skill-building courses to prisoners so that they can rehabilitate themselves in society after their release. Counselling programs and awareness of legal aid programs provide a supportive hand to the prisoners. AI can provide different types of counseling programs based on the prisoners' psychological behavior. The various other aspects of rehabilitation programs, such as AI-generated courses, can lead prisoners to live in society in a dignified manner. All these aspects will be discussed in this research paper. Prisoner rehabilitation is a debated issue in the criminal justice delivery system. Now recidivism of prisoners is a serious issue that must be reduced. It can be reduced by way of rehabilitation of prisoners so that prisoners can reintegrate into society. In the present era, artificial intelligence (AI) can change the way to transform the efforts of rehabilitation of prisoners in India. Prisoners face various issues living in society, such as a lack of financial resources, overcrowding, and a lack of rehabilitation programs. The working method of AI can help the rehabilitation of prisoners, which lowers the recidivism rates in India. Psychological testing, vocational training and individualized rehabilitation programs are the main aspects of rehabilitation of prisoners. Artificial intelligence includes various tools such as language processing, machine learning, and predictive analytics to help psychological testing, vocational training, and rehabilitation programmes. The authorities cannot understand the psychological facts and inmate behaviour of prisoners. AI-based learning: the concept of virtual reality can provide skill-building courses to prisoners so that they can rehabilitate themselves in society after their release. Counselling programs and awareness of legal aid programs provide a supportive hand to the prisoners. AI can provide different types of counselling programmes based on the psychological behaviour of the prisoners. The various other aspects of rehabilitation programmes, such as AI-generated courses, can lead the prisoners to live in society in a dignified manner. All these aspects will be discussed in this research paper.
Keywords Artificial Intelligence, Prisoner Rehabilitation, Recidivism, Criminal Justice System, Virtual Reality
Field Sociology > Administration / Law / Management
Published In Volume 8, Issue 5, September-October 2026
Published On 2026-09-23
DOI https://doi.org/10.36948/ijfmr.2026.v08i05.87682

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