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Guardians Of Tomorrow: A Futuristic Approach To Indian Policing Through Adequate Deployment Of Artificial Intelligence & Machine Learning




Navneet Jain, B.A.LL.B., Pursuing LL.M., Gujarat National Law University, Gandhinagar, Gujarat


ABSTRACT


Indian police force is the second largest police force in the world in terms of number of personnels, just beside China. However, in terms of total population, India has already overtaken China and is now the most populous country in the world. To police on such a wide scale of population is definitely a challenging task. And, to assist in this crucial task, technology such as Artificial Intelligence (AI) and Machine Learning (ML) can be of immense help. AI can assist the police department in performing important functions such as surveillance, intelligence collection, prevention and detection of crime etc. AI can be useful in different kinds like Predictive policing and nabbing criminals through facial recognition. However, police department in India is not adequately equipped with the usage of AI and ML technology. This paper will make sincere effort to address this issue. The research will delve into the important role, induction of AI can play in making Indian police department more effective, efficient and future ready. Successful examples of adoption of AI technology by police departments across different states of India shall be drawn. This research will also examine the best AI-ML practices deployed by different countries across the globe. Lastly, research will make an effort to identify and address the challenges in adoption and implementation of AI and ML technology in police departments across different states of India.


Keywords: Artificial Intelligence (AI), Machine Learning (ML), Technology, Police

Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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Licensing: 

 

All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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