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The Moral Dilemma: Assessing The Ethical Implications Of AI-Assisted Sentencing In Criminal Justice


 


Dr. Priyadarshi Nagda, Assistant Professor, University College of Law, MLSU, Saheli Nager, Udaipur


ABSTRACT


Integrating artificial intelligence (AI) in criminal justice, particularly sentencing has sparked significant debate regarding its ethical implications, benefits, and challenges. This paper explores the impact of AI-assisted sentencing on judicial efficiency, consistency, and fairness while addressing concerns about bias, transparency, and privacy. By analyzing secondary data from the Supreme Court of India, the study assesses the effectiveness of AI in reducing sentencing disparities and improving case resolution times. The findings highlight the potential of AI to enhance judicial processes by providing data-driven insights, promoting equitable outcomes, and expediting case resolutions. However, the study also emphasizes the need for a robust legal and ethical framework to mitigate biases, ensure transparency, and protect individual privacy rights. It underscores the importance of maintaining human discretion in sentencing decisions to preserve justice's moral and ethical dimensions. The paper concludes with recommendations for future research, focusing on developing fair and interpretable AI models, addressing data quality issues, and establishing comprehensive guidelines for the responsible use of AI in the judicial system.


Keywords: AI-assisted sentencing, criminal justice, judicial efficiency, ethical implications.



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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