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Liked our Work? Search it now on IndoPacific.App Get Searching Our Research Know more about our Knowledge Base, years of accumulated and developed in-house research at Indic Pacific Legal Research. Search our Research Treasure on IndoPacific.App. :) Global Relations and Legal Policy, Volume 2 Get this Publication 2021 ISBN 978-81-947926-4-2 Author(s) Adrija Ghosh, Anirudh Vats, Beghuman Simsir, Chitrika Grover, Hriti Parekh, Ishita Thakur, Mahak Gupta, Manohar Samal, Nikita Mulay, Sameep Khanal, Sanchana Srivastava, Srishti Pareek, Subodh Singh Editor(s) Abhivardhan IndoPacific.App Identifier (ID) GRLP2 Tags International Law, Public Policy Related Terms in Techindata.in Explainers Definitions - A - E CEI Classification Class-of-Applications-by-Class-of-Application (CbC) approach Definitions - F - J GAE Indo-Pacific International Algorithmic Law Definitions - K - P Multi-alignment Multipolar World Multipolarity Permeable Indigeneity in Policy (PIP) Phenomena-based concept classification Definitions - Q - U Strategic Autonomy Strategic Hedging Technophobia Definitions - V - Z WANA WENA Whole-of-Government Response Related Articles in Techindata.in Insights 4 Insight(s) on Government Affairs 1 Insight(s) on India-US Relations 1 Insight(s) on governance 1 Insight(s) on Indic Pacific 1 Insight(s) on India 1 Insight(s) on strategic sectors . Previous Item Next Item

Issued by the Department of Expenditure in February 2025, this communication determined that AI tools and AI apps in office computers and devices pose risks to the confidentiality of government data and documents. The advisory strictly prohibits employees from using any AI tools or apps in office devices. This represents a complete ban approach similar to ESIC's policy but applied across the Finance Ministry.​ India AI Regulation Landscape 101 This is a simple regulatory tracker consisting all information on how India is regulating artificial intelligence as a technology, inspired from a seminal paper authored by Abhivardhan and Deepanshu Singh for the Forum of Federations, Canada, entitled, "Government with Algorithms: Managing AI in India’s Federal System – Number 70 ". We have also included case laws along with regulatory / governance documents, and avoided adding any industry documents or policy papers which do not reflect any direct or implicit legal impact. Advisory on Prohibition of AI Tools/Apps in Office Devices Issued by the Department of Expenditure in February 2025, this communication determined that AI tools and AI apps in office computers and devices pose risks to the confidentiality of government data and documents. The advisory strictly prohibits employees from using any AI tools or apps in office devices. This represents a complete ban approach similar to ESIC's policy but applied across the Finance Ministry. Previous Next February 2025 Issuing Authority Ministry of Finance, Department of Expenditure Type of Legal / Policy Document Executive Instruments - Administrative Decisions Status In Force Regulatory Stage Regulatory Binding Value Legally binding instruments enforceable before courts Read the Document AI Regulation Visualisation Related Long-form Insights on IndoPacific.App Reimaging and Restructuring MeiTY for India [IPLR-IG-007] Learn More Averting Framework Fatigue in AI Governance [IPLR-IG-013] Learn More Decoding the AI Competency Triad for Public Officials [IPLR-IG-014] Learn More AI Bias & the Overlap of AI Diplomacy and Governance Ethics Dilemmas Learn More Artificial Intelligence, Market Power and India in a Multipolar World Learn More Related draft AI Law Provisions of aiact.in Section 15 – Guidance Principles for AI-related Agreements Section 15 – Guidance Principles for AI-related Agreements Section 16 – Guidance Principles for AI-related Corporate Governance Section 16 – Guidance Principles for AI-related Corporate Governance

Federated Learning Explainers The Complete Glossary terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com Federated Learning Date of Addition 22 March 2025 A decentralised machine learning approach where multiple organizations or devices train models collaboratively without sharing raw data. Instead, only model updates or parameters are exchanged, ensuring data privacy while leveraging distributed data for improved model accuracy. Federated learning involves a two-step process: during training, local models are trained on local datasets with only parameters (not raw data) exchanged between participants to build a global model; during inference, the model is stored on the user device for quick predictions. This approach offers several advantages: privacy-preserving AI development, personalised and adaptive models, lower bandwidth usage, and improved security through decentralisation. Related Long-form Insights on IndoPacific.App Reinventing & Regulating Policy Use Cases of Web3 for India [VLiGTA-TR-004] Learn More Previous Term Next Term

Retrieval-Augmented Generation (RAG) Date of Addition 17 October 2025 A hybrid AI framework that combines large language models with external information retrieval systems to generate responses grounded in authoritative, real-time data sources rather than relying solely on static training data. RAG operates by fetching relevant documents from databases, knowledge bases, or repositories before the LLM generates output, thereby reducing hallucinations, improving factual accuracy, and enabling domain-specific responses without costly model retraining. The technique addresses fundamental LLM limitations including outdated information, terminology confusion, and inability to access proprietary organizational knowledge. Related Long-form Insights on IndoPacific.App Deciphering Regulative Methods for Generative AI [VLiGTA-TR-002] Learn More NIST Adversarial Machine Learning Taxonomies: Decoded, IPLR-IG-016 Learn More Previous Term Next Term Explainers The Complete Glossary terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com

Privacy by Design Date of Addition 26 April 2024 Privacy by Design states that any action a company undertakes that involves processing personal data must be done with data protection and privacy in mind at every step. This was largely proposed in the Article 25 of the General Data Protection Regulation of the European Union. Related Long-form Insights on IndoPacific.App 2021 Handbook on AI and International Law [RHB 2021 ISAIL] Learn More Deciphering Artificial Intelligence Hype and its Legal-Economic Risks [VLiGTA-TR-001] Learn More Reinventing & Regulating Policy Use Cases of Web3 for India [VLiGTA-TR-004] Learn More [Version 1] A New Artificial Intelligence Strategy and an Artificial Intelligence (Development & Regulation) Bill, 2023 Learn More [Version 2] Draft Artificial Intelligence (Development & Regulation) Act, 2023 Learn More [AIACT.IN V3] Draft Artificial Intelligence (Development & Regulation) Act, 2023, Version 3 Learn More AIACT.IN Version 3 Quick Explainer Learn More Sections 4-9, AiACT.IN V4 Infographic Explainers Learn More [AIACT.IN V4] Draft Artificial Intelligence (Development & Regulation) Act, 2023, Version 4 Learn More [AIACT.IN V5] Draft Artificial Intelligence (Development & Regulation) Act, 2023, Version 5 Learn More Reckoning the Viability of Safe Harbour in Technology Law, IPLR-IG-015 Learn More Indo-Pacific Research Ethics Framework on Artificial Intelligence Use [IPac AI] Learn More NIST Adversarial Machine Learning Taxonomies: Decoded, IPLR-IG-016 Learn More Normative Emergence in Cyber Geographies: International Algorithmic Law in a Multipolar Technological Order, First Edition Learn More AI Bias & the Overlap of AI Diplomacy and Governance Ethics Dilemmas Learn More 2020 Handbook on AI and International Law [RHB 2020 ISAIL] Learn More Previous Term Next Term Explainers The Complete Glossary terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com

Technophobia Date of Addition 19 January 2025 An irrational or disproportionate fear, aversion, or resistance to advanced technologies, technological change, and digital innovation. Manifests as psychological and physiological responses ranging from mild anxiety to severe distress when interacting with or contemplating technological systems. Often characterised by: Cognitive resistance to learning new technological skills Physical symptoms when forced to use technology Avoidance behaviours toward digital tools and platforms Distinguished from rational technology criticism by its emotional rather than analytical basis. Particularly relevant in contexts of rapid technological transformation, AI adoption, and digital transformation initiatives. Related Long-form Insights on IndoPacific.App Global Customary International Law Index: A Prologue [GLA-TR-00X] Learn More Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] Learn More India-led Global Governance in the Indo-Pacific: Basis & Approaches [GLA-TR-003] Learn More Regulatory Sandboxes for Artificial Intelligence: Techno-Legal Approaches for India [ISAIL-TR-002] Learn More Global Legalism, Volume 1 Learn More Global Relations and Legal Policy, Volume 1 [GRLP1] Learn More South Asian Review of International Law, Volume 1 Learn More Indian International Law Series, Volume 1 Learn More Global Relations and Legal Policy, Volume 2 Learn More Deciphering Artificial Intelligence Hype and its Legal-Economic Risks [VLiGTA-TR-001] Learn More Deciphering Regulative Methods for Generative AI [VLiGTA-TR-002] Learn More Promoting Economy of Innovation through Explainable AI [VLiGTA-TR-003] Learn More Reinventing & Regulating Policy Use Cases of Web3 for India [VLiGTA-TR-004] Learn More Auditing AI Companies for Corporate Internal Investigations in India, VLiGTA-TR-005 Learn More The Policy Purpose of a Multipolar Agenda for India, First Edition, 2023 Learn More Artificial Intelligence Governance using Complex Adaptivity: Feedback Report, First Edition, 2024 Learn More Legal Strategies for Open Source Artificial Intelligence Practices, IPLR-IG-004 Learn More Artificial Intelligence and Policy in India, Volume 4 [AIPI-V4] Learn More Ethical AI Implementation and Integration in Digital Public Infrastructure, IPLR-IG-005 Learn More The Indic Approach to Artificial Intelligence Policy [IPLR-IG-006] Learn More Artificial Intelligence and Policy in India, Volume 5 [AIPI-V5] Learn More Indic Pacific - ISAIL Joint Annual Report, 2022-24 Learn More The Legal and Ethical Implications of Monosemanticity in LLMs [IPLR-IG-008] Learn More Navigating Risk and Responsibility in AI-Driven Predictive Maintenance for Spacecraft, IPLR-IG-009, First Edition, 2024 Learn More Impact-Based Legal Problems around Generative AI in Publishing, IPLR-IG-010 Learn More Legal-Economic Issues in Indian AI Compute and Infrastructure, IPLR-IG-011 Learn More Averting Framework Fatigue in AI Governance [IPLR-IG-013] Learn More Decoding the AI Competency Triad for Public Officials [IPLR-IG-014] Learn More The Global AI Inventorship Handbook, First Edition [RHB-AI-INVENT-001-2025] Learn More Normative Emergence in Cyber Geographies: International Algorithmic Law in a Multipolar Technological Order, First Edition Learn More AI Bias & the Overlap of AI Diplomacy and Governance Ethics Dilemmas Learn More Artificial Intelligence and Policy in India, Volume 6 [AIPI-V6] Learn More Artificial Intelligence, Market Power and India in a Multipolar World Learn More Previous Term Next Term Explainers The Complete Glossary terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com

Section 14 – Model Standards on Knowledge Management PUBLISHED Previous Next Section 14 - Model Standards on Knowledge Management (1) The IAIC shall develop, document and promote comprehensive model standards on knowledge management practices concerning the development, maintenance, and governance of high-risk AI systems. These standards shall focus on the effective management of knowledge assets; (2) The model standards shall encompass the following areas: (i) Intellectual property management practices to safeguard and leverage AI-related intellectual property rights such as patents, copyrights, trademarks and industrial designs. (ii) Processes for documenting and organizing technical knowledge assets like research reports, manuals, standards and industrial practices related to AI systems. (iii) Frameworks for capturing, retaining and transferring the tacit knowledge and expertise of human capital involved in AI development and deployment. (iv) Organisational systems and methodologies to enable effective knowledge capture, storage, retrieval and utilisation across the AI system lifecycle. (v) Mechanisms for leveraging customer-related knowledge assets such as data, feedback and insights to enhance AI system development and performance. (vi) Analytical techniques to derive knowledge from data analysis, including identifying patterns, trends and developing predictive models for AI systems. (vii)Collaborative practices to foster cross-functional knowledge sharing and generation through teams, communities of practice and other initiatives. (3) All entities engaged in the development, deployment, or utilisation of high-risk AI systems shall be bound by the model standards on knowledge management and decision-making as provided by this section. The compliance timeline for such high-risk AI systems shall be determined by the IAIC and may vary based on the technical, commercial and risk-based classification of those systems under Section 12. (4) For artificial intelligence technologies subject to commercial classification as determined by the factors outlined in sub-section (1) of Section 6, the requirement to comply with these model standards on knowledge management shall be assessed by the IAIC on a case-by-case basis, taking into consideration the specific commercial classification factors applicable to each AI technology. Illustration A startup has developed an AI-powered language translation app that allows users to translate text, documents, and speech between multiple Indian languages. Based on an assessment of the factors in Section 6(1), such as the app’s user base, market influence, and data integration, the IAIC may determine that this AI technology falls under the AI-Pro or AIaaS category. The IAIC will then evaluate if the startup needs to fully comply with the knowledge management standards or if certain requirements can be relaxed or made optional based on the app’s specific use case and commercial profile. (5) In determining the case-by-case application of these model standards to commercially classified AI technologies under sub-section (1) of Section 6, the IAIC shall take into account any relevant sector-specific standards, codes of practice, or regulatory guidelines pertaining to knowledge management practices in the sector to which the AI technology belongs or is intended to be deployed. Illustration An agritech startup has developed an AI system that analyzes satellite imagery and weather data to provide crop yield predictions and advisory services to farmers. As this AI technology falls within the agriculture sector, the IAIC’s assessment of its knowledge management requirements will consider any relevant guidelines or standards issued by bodies like the Indian Council of Agricultural Research (ICAR) or the Ministry of Agriculture & Farmers’ Welfare. These may include data governance norms for agricultural data, model validation protocols for AI-based advisory services, or best practices for maintaining data trails and audit logs in agritech applications. (6) Failure to adhere to the prescribed model standards for knowledge management and decision-making processes shall result in regulatory actions by the IAIC, which may include: (i) Issuance of show-cause notices to the non-compliant entity, requiring them to explain the reasons for non-compliance and outline corrective measures within a specified timeline. (ii) Imposition of monetary penalties, determined based on the severity of non-compliance, the risk level of the AI system involved, and the potential impact on individuals, businesses, or society. The monetary penalties shall be commensurate with the financial capacity of the non-compliant entity. (iii)Suspension or revocation of certifications or registrations related to the non-compliant AI system, preventing its further development, deployment, or operation until compliance is achieved. (iv) Mandating independent audits of the non-compliant entity’s knowledge management and decision-making processes at their own cost, with the audit reports to be submitted to the IAIC for review and further action. (v) Issuing directives to the non-compliant entity to implement specific remedial measures, such as enhancing data quality controls, improving model governance frameworks, or strengthening decision-making procedures, within a defined timeline. (vi) In cases of persistent or egregious non-compliance, the IAIC may recommend the temporary or permanent suspension of the non-compliant entity’s AI-related operations, subject to due process and the principles of natural justice. (vii) Any other regulatory action deemed necessary and proportionate by the IAIC to ensure compliance with the prescribed model standards and to safeguard the responsible development, deployment, and use of high-risk AI systems. (7) The IAIC shall encourage the sharing of AI-related knowledge, including datasets, models, and algorithms, through open-source software repositories and platforms, subject to applicable intellectual property rights and the provisions of the Digital Personal Data Protection Act, 2023 and other relevant data protection and governance frameworks as may be prescribed. Related Indian AI Regulation Sources National Strategy for Artificial Intelligence (#AIforAll) June 2018

Liked our Work? Search it now on IndoPacific.App Get Searching Our Research Know more about our Knowledge Base, years of accumulated and developed in-house research at Indic Pacific Legal Research. Search our Research Treasure on IndoPacific.App. :) Impact-Based Legal Problems around Generative AI in Publishing, IPLR-IG-010 Get this Publication 2024 ISBN 978-81-977227-6-9 Author(s) Abhivardhan, Alisha Garg, Samyak Deshpande, Sanvi Zadoo Editor(s) Not Applicable IndoPacific.App Identifier (ID) IPLR-IG-010 Tags Abhivardhan, Accountability, AI, AI Ethics, AI Patentability, AI-assisted invention, AI-generated code, AI-generated content, AI-generated images, AI-generated invention, AI-generated music, AI-generated text, bias, context-specific AI governance, Copyright, copyright infringement, copyright transfer, creative commons, deepfakes, derivative work, disinformation, fair dealing, Fair Use, Generative AI, Governance, infringement threshold, Intellectual Property, inventorship, Licensing, misinformation, moral rights, non-obviousness, novelty, Open Source, original work, patent eligibility, patent examination, patent infringement, patent law, prior art, public disclosure, public domain, publishing, RBI FREE-AI Committee, regulation, statutory bars, substantial similarity, Transparency, utility Related Terms in Techindata.in Explainers Definitions - A - E AI Agents AI Anxiety AI Explainability Clause AI Knowledge Chain AI Literacy AI Supply Chain AI Value Chain Accountability Automation Definitions - F - J General intelligence applications with multiple short-run or unclear use cases as per industrial and regulatory standards (GI2) General intelligence applications with multiple stable use cases as per relevant industrial and regulatory standards (GI1) Generative AI applications with one standalone use case (GAI1) In-context Learning Indofuturism Intended Purpose / Specified Purpose Definitions - K - P Language Model Manifest Availability Model Algorithmic Ethics standards (MAES) Multivariant, Fungible & Disruptive Use Cases & Test Cases of Generative AI Object-Oriented Design Proprietary Information Definitions - Q - U Roughdraft AI SOTP Classification Synthetic Content Technical concept classifcation Technology by Default Technology by Design Technology Distancing Technology Transfer Technophobia Definitions - V - Z Whole-of-Government Response Related Articles in Techindata.in Insights 29 Insight(s) on AI Ethics 8 Insight(s) on AI and Copyright Law 7 Insight(s) on AI and Competition Law 7 Insight(s) on AI and media sciences 7 Insight(s) on AI regulation 5 Insight(s) on AI Governance 3 Insight(s) on AI and Evidence Law 3 Insight(s) on AI literacy 2 Insight(s) on Abhivardhan 2 Insight(s) on AI and Intellectual Property Law 1 Insight(s) on AI and Securities Law 1 Insight(s) on Algorithmic Trading . Previous Item Next Item

AI Workflows Explainers The Complete Glossary AI Workflows Date of Addition 19 Jan 2025 A structured automation process that integrates Artificial Intelligence, such as Large Language Models (LLMs) like ChatGPT, into specific steps via APIs. AI workflows are ideal for deterministic tasks requiring flexibility, pattern recognition, or the handling of complex rules. They combine traditional automation with AI-enhanced decision-making to address more dynamic needs. Related Long-form Insights on IndoPacific.App Artificial Intelligence Governance using Complex Adaptivity: Feedback Report, First Edition, 2024 Learn More Legal Strategies for Open Source Artificial Intelligence Practices, IPLR-IG-004 Learn More Ethical AI Implementation and Integration in Digital Public Infrastructure, IPLR-IG-005 Learn More Reimaging and Restructuring MeiTY for India [IPLR-IG-007] Learn More Reckoning the Viability of Safe Harbour in Technology Law, IPLR-IG-015 Learn More Previous Term Next Term terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com

Delhi High Court October 2025 judgment protecting Bollywood actor Hrithik Roshan's personality rights against AI-generated deepfakes, morphed content, and unauthorized merchandise exploitation while exempting non-commercial fan pages from blanket takedown orders. Significantly, the court balanced personality rights protection with fan expression by declining to order immediate takedown of fan pages, noting they use the actor's image for non-commercial purposes. India AI Regulation Landscape 101 This is a simple regulatory tracker consisting all information on how India is regulating artificial intelligence as a technology, inspired from a seminal paper authored by Abhivardhan and Deepanshu Singh for the Forum of Federations, Canada, entitled, "Government with Algorithms: Managing AI in India’s Federal System – Number 70 ". We have also included case laws along with regulatory / governance documents, and avoided adding any industry documents or policy papers which do not reflect any direct or implicit legal impact. Hrithik Roshan v. Ashok Kumar/John Doe & Ors., CS(COMM) 1107/2025, Delhi High Court, Order dated October 15, 2025 Delhi High Court October 2025 judgment protecting Bollywood actor Hrithik Roshan's personality rights against AI-generated deepfakes, morphed content, and unauthorized merchandise exploitation while exempting non-commercial fan pages from blanket takedown orders. Significantly, the court balanced personality rights protection with fan expression by declining to order immediate takedown of fan pages, noting they use the actor's image for non-commercial purposes. Previous Next October 2025 Issuing Authority Delhi High Court Type of Legal / Policy Document Judicial Pronouncements - National Court Precedents Status In Force Regulatory Stage Regulatory Binding Value Legally binding instruments enforceable before courts Read the Document AI Regulation Visualisation Related Long-form Insights on IndoPacific.App Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] Learn More Impact-Based Legal Problems around Generative AI in Publishing, IPLR-IG-010 Learn More Indo-Pacific Research Ethics Framework on Artificial Intelligence Use [IPac AI] Learn More The Global AI Inventorship Handbook, First Edition [RHB-AI-INVENT-001-2025] Learn More Related draft AI Law Provisions of aiact.in Section 21 – Intellectual Property Protections Section 21 – Intellectual Property Protections Section 23 – Content Provenance and Identification Section 23 – Content Provenance and Identification

AI Supply Chain Explainers The Complete Glossary AI Supply Chain Date of Addition 5 Mar 2025 The end-to-end network of resources, technologies, infrastructures, and services required to create, train, deploy, and maintain AI systems. This includes hardware components (processing units, memory, sensors), computational resources (cloud services, data centres), data resources (datasets, knowledge bases), algorithmic frameworks, and human expertise. The AI supply chain encompasses both tangible and intangible assets across global networks of providers that collectively enable AI capabilities for end-users and organisations. Related Long-form Insights on IndoPacific.App Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] Learn More Regulatory Sovereignty in India: Indigenizing Competition-Technology Approaches [ISAIL-TR-001] Learn More Artificial Intelligence Governance using Complex Adaptivity: Feedback Report, First Edition, 2024 Learn More Draft Digital Competition Bill, 2024 for India: Feedback Report [IPLR-IG-003] Learn More Legal Strategies for Open Source Artificial Intelligence Practices, IPLR-IG-004 Learn More Artificial Intelligence and Policy in India, Volume 4 [AIPI-V4] Learn More Ethical AI Implementation and Integration in Digital Public Infrastructure, IPLR-IG-005 Learn More Reimaging and Restructuring MeiTY for India [IPLR-IG-007] Learn More Indic Pacific - ISAIL Joint Annual Report, 2022-24 Learn More Impact-Based Legal Problems around Generative AI in Publishing, IPLR-IG-010 Learn More Legal-Economic Issues in Indian AI Compute and Infrastructure, IPLR-IG-011 Learn More Reckoning the Viability of Safe Harbour in Technology Law, IPLR-IG-015 Learn More Indo-Pacific Research Ethics Framework on Artificial Intelligence Use [IPac AI] Learn More Artificial Intelligence and Policy in India, Volume 6 [AIPI-V6] Learn More Previous Term Next Term terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com

Derivative Generative AI Applications, the Generative AI products and services which are derivatives of the main generative AI applications, by virtue of reliance (DGAI) Explainers The Complete Glossary Derivative Generative AI Applications, the Generative AI products and services which are derivatives of the main generative AI applications, by virtue of reliance (DGAI) Date of Addition 26 Apr 2024 This is an ontological sub-category of Generative AI applications which implies that a Generative AI application could be built on the basis of a training model, any API or any commercial or technical component of another AI or Generative AI application. Such an application could be called as a Derivative Generative AI Application. This idea was proposed in Deciphering Regulative Methods for Generative AI, VLiGTA-TR-002 (2023). Related Long-form Insights on IndoPacific.App Deciphering Regulative Methods for Generative AI [VLiGTA-TR-002] Learn More Artificial Intelligence, Market Power and India in a Multipolar World Learn More Previous Term Next Term terms of use This glossary of terms is provided as a free resource for educational and informational purposes only. By using this glossary developed by Indic Pacific Legal Research LLP (referred to as 'The Firm'), you agree to the following terms of use: You may use the glossary for personal and non-commercial purposes only. If you use any content from the glossary of terms on this website in your own work, you must properly attribute the source. This means including a link to this website and citing the title of the glossary. Here is a sample format to cite this glossary (we have used the OSCOLA citation format as an example): Indic Pacific Legal Research LLP, 'TechinData.in Explainers' (Indic Pacific Legal Research , 2023) You are not authorised to reproduce, distribute, or modify the glossary without the express written permission of a representative of Indic Pacific Legal Research. The Firm makes no representations or warranties about the accuracy or completeness of the glossary. The glossary is provided on an "as is" basis and the Firm disclaims all liability for any errors or omissions in the glossary. You agree to indemnify and hold the Firm harmless from any claims or damages arising out of your use of the glossary. If you have any questions or concerns about these terms of use, please contact us at global@indicpacific.com