kulawrKutafin Law ReviewKutafin Law Review2713-05252713-0533MSAL10.17803/2713-0533.2026.2.36.237-268kulawr-882Research ArticleARTIFICIAL INTELLIGENCE, DIGITAL TECHNOLOGIES & DATA GOVERNANCEFrom Data Mining to Copyright Infringement: Legal Challenges in Training Artificial Intelligencehttps://orcid.org/0009-0001-2297-0409BadkulS.

Siddharth Badkul , PhD, Research Scholar; Assistant Professor of Law

Nagpur; Greater Noida

siddharthbadkul@gmail.comMaharashtra National Law University ; Bennett UniversityIndia202617072026132237268Copyright © Badkul S., 20262026Badkul S.Badkul S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://kulawr.msal.ru/jour/article/view/882

Legal controversies pertaining to the use of copyrighted material in artificial intelligence training datasets have been fuelled by the fast development of large language models. The paper explores the complex legal issues resulting from data mining activities and possible copyright violations associated with the training of AI. The paper includes the technological perspective of data mining and training of AI models. Further, the paper deals with the legal challenges, scrutinising whether specific technological methods such as the use of unrecognisable examples, watermarking techniques, machine unlearning, dataset de-duplication, etc., thereby exploring how their application prevents copyright infringement. As original contributions, the paper analyses the theories related to copyright law and evaluates the effectiveness of the aforementioned technological method in fulfilling the objectives of these theories. The paper provides an original framework of assessment of copyright issues in AI training datasets, by contrasting systems in the EU, U.S., and India. It reveals regulatory loopholes in the copyright law in India and suggests a hybridized approach to Indian copyright law, the Fair Learning Doctrine that combines the concepts of transformative use and proportionality. The paper adopts a doctrinal and analytical approach, analysing case laws, statutory interpretation, and technological literature to assess the relationship between AI and copyright vis-à-vis training of AI model.

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The authors declare that there are no conflicts of interest present.