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When The Algorithm Audits You: Human Rights Implications Of Artificial Intelligence In Taxation With Special Reference To India And Comparative Perspectives From The EU And US

May 26
1 min read



Diya Pundir, Uttaranchal University, Law College Dehradun

Satyam Sharma, Assistant Professor, Uttaranchal University, Law College Dehradun


ABSTRACT


The world is racing to adopt artificial intelligence (AI) in taxation to combat evasion, automate tax assessments, identify anomalies and develop tax profiles. India is not immune - the Income Tax Department's use of AI-based risk profiling, the Faceless Assessment Scheme and data analytics (Project Insight) are a major expansion of the state's revenue powers. This increase in algorithmic power in taxation not only has implications for administrative efficiency, but also for the right to equality, the right against arbitrary state action, the right to privacy, the right to a fair hearing, and the prohibition on discriminatory enforcement. This article explores these human rights concerns in detail, with reference to the Indian Constitution and some comparative case studies in the European Union and US. It concludes that the use of AI in taxation, although legitimate in principle, necessitates robust legal protections that are not yet in place - particularly in India.


Keywords: Artificial Intelligence, Taxation, Human Rights, Right to Privacy, Algorithmic Decision-Making, Faceless Assessment, Article 14, Due Process, India, EU, United States.



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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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.

 

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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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