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Section 33 – Savings Clause PUBLISHED Previous Next Section 33 - Savings Clause (1) The provisions of this Act shall be in addition to, and not in derogation of, the provisions of any other law for the time being in force. (2) Nothing in this Act shall affect the validity of any action taken or decision made by any entity in relation to the development, deployment, or use of AI systems prior to the commencement of this Act, provided such action or decision was in accordance with the laws in force at that time. (3) Any investigation, legal proceeding, or remedy in respect of any right, privilege, obligation, liability, penalty, or punishment under any law, initiated or arising before the commencement of this Act, shall be continued, enforced, or imposed as if this Act had not been enacted. (4) Nothing in this Act shall be construed as preventing the Central Government from making any rules or regulations, or taking any action, which it considers necessary for the purpose of removing any difficulty that may arise in giving effect to the provisions of this Act. Related Indian AI Regulation Sources

Zero Knowledge Taxes Date of Addition 26 April 2024 Zero-knowledge taxes (ZKTs) are a hypothetical type of tax that could be implemented using ZKSs. ZKTs would allow taxpayers to prove to the government that they have paid their taxes without revealing their income or other financial information. This was discussed in Reinventing & Regulating Policy Use Cases of Web3 for India, VLiGTA-TR-004 (2023). Related Long-form Insights on IndoPacific.App Reinventing & Regulating Policy Use Cases of Web3 for India [VLiGTA-TR-004] Learn More Next Term Previous Term The Indic Pacific Glossary 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 12 – National Registry of Artificial Intelligence Use Cases PUBLISHED Previous Next Section 12 – National Registry of Artificial Intelligence Use Cases (1) The National Registry of Artificial Intelligence Use Cases shall include the metadata for each registered AI system as set forth in sub-sections (1)(i) through (1)(xvi): (i) Name and version of the AI system (required) (ii) Owning entity of the AI system (required) (iii) Date of registration (required) (iv) Sector associated with the AI system and whether the AI system is associated with a strategic sector (required) (v) Specific use case(s) of the AI system (required) (vi) Technical classification of the AI system, as per Section 5 (required) (vii)Key technical characteristics of the AI system as per Section 5, including: (a) Type of AI model(s) used (required) (b) Training data sources and characteristics (required) (c) Performance metrics on standard benchmarks (where available, optional) (viii) Commercial classification of the AI system as per Section 6 (required) (ix) Key commercial features of the AI system as per Section 6, including: (a) Number of end-users and business end-users in India (required, where applicable) (b) Market share or level of market influence in the intended sector(s) of application (required, where ascertainable) (c) Annual turnover or revenue generated by the AI system or the company owning it (required, where applicable) (d) Amount & intended purpose of data collected, processed, or utilized by the AI system (required, where measurable) (e) Level of data integration across different services or platforms (required, where applicable) (x) Risk classification of the AI system as per Section 7 (required) (xi) Conceptual classification of the AI system as per Section 4 (required only for high-risk AI Systems) (xii) Potential impacts of the AI system as per Section 7, including: (a) Inherent Purpose (required) (b) Possible risks and harms observed and documented by the owning entity (required) (xiii) Certification status (required) (registered & certified / registered & not certified) (xiv) A detailed post-deployment monitoring plan as per Section 17 (required only for high-risk AI Systems), including: (a) Performance metrics and key indicators to be tracked (optional) (b) Risk mitigation and human oversight protocols (required) (c) Data collection, reporting, and audit trail mechanisms (required) (d) Feedback and redressal channels for impacted stakeholders (optional) (e) Commitments to periodic third-party audits and public disclosure of: (i) Monitoring reports and performance indicators (optional) (ii) Descriptions of identified risks, incidents or failures as per sub-section (3) of Section 17 (required) (iii) Corrective actions and mitigation measures implemented (required) (xv) Incident reporting and response protocols as per Section 19 (required) (a) Description of the incident reporting mechanisms established (e.g. hotline, online portal) (b) Timelines committed for incident reporting based on risk classification (c) Procedures for assessing and determining incident severity levels (d) Information to be provided in incident reports as per guidelines (e) Confidentiality and data protection measures for incident data (f) Minimum mitigation actions to be taken upon incident occurrence (g) Responsible personnel/team for incident response and mitigation (h) Commitments on notifying and communicating with impacted parties (i) Integration with IAIC’s central incident repository and reporting channels (j) Review and improvement processes for incident response procedures (k) Description of the insurance coverage obtained for the AI system, as per Section 25, including the type of policy, insurer, policy number, and coverage limits; (l) Confirmation that the insurance coverage meets the minimum requirements specified in the sub-section (3) of Section 25 based on the AI system’s risk classification; (m) Details of the risk assessment conducted to determine the appropriate level of insurance coverage, considering factors such as the AI system’s conceptual, technical, and commercial classifications as per Sections 4, 5, and 6; (n) Information on the claims process and timelines for notifying the insurer and submitting claims in the event of an incident covered under the insurance policy; (o) Commitment to maintain the insurance coverage throughout the lifecycle of the AI system and to notify the IAIC of any changes in coverage or insurer. (xvi) Contact information for the owning entity (required) Illustration A technology company develops a new AI system for automated medical diagnosis using computer vision and machine learning techniques. This AI system would be classified as a high-risk system under Section 7(4) due to its potential impact on human health and safety. The company registers this AI system in the National Registry of Artificial Intelligence Use Cases, providing the following metadata: (i) Name and version: MedVision AI Diagnostic System v1.2 (ii) Owning entity: ABC Technologies Pvt. Ltd. (iii) Date of registration: 01/05/2024 (iv) Sector: Healthcare (v) Use case: Automated analysis of medical imaging data (X-rays, CT scans, MRIs) to detect and diagnose diseases (vi) Technical classification: Specific Purpose AI (SPAI) under Section 5(4) (vii) Key technical characteristics: · Convolutional neural networks for image analysis · Trained on de-identified medical imaging datasets from hospitals · Achieved 92% accuracy on standard benchmarks (viii) Commercial classification: AI-Pro under Section 6(3) (ix) Key commercial features: · Intended for use by healthcare providers across India · Not yet deployed, so no market share data · No revenue generated yet (pre-commercial) (x) Risk classification: High Risk under Section 7(4) (xi) Conceptual classification: Assessed under all four methods in Section 4 due to high-risk (xii) Potential impacts: · Inherent purpose is to assist medical professionals in diagnosis · Documented risks include misdiagnosis, bias, lack of interpretability (xiii) Certification status: Registered & certified (xiv) Post-deployment monitoring plan: · Performance metrics like accuracy, false positive/negative rates · Human oversight, periodic audits for bias/errors · Logging all outputs, decisions for audit trail · Channels for user feedback, grievance redressal · Commitments to third-party audits, public incident disclosure (xv) Incident reporting protocols: · Dedicated online portal for incident reporting · Critical incidents to be reported within 48 hours · High/medium severity incidents within 7 days · Procedures for severity assessment, confidentiality measures · Minimum mitigation actions, impacted party notifications · Integration with IAIC incident repository · Insurance coverage details: · Professional indemnity policy from XYZ Insurance Co., policy #PI12345 · Coverage limit of INR 50 crores, as required for high-risk AI under Section 25(3)(i) · Risk assessment considered technical complexity, healthcare impact, irreversible consequences · Claims to be notified within 24 hours, supporting documentation within 7 days · Coverage to be maintained throughout AI system lifecycle, IAIC to be notified of changes (xvi) Contact : info@abctech.com (2) The IAIC may, from time to time, expand or modify the metadata schema for the National Registry as it deems necessary to reflect advancements in AI technology and risk assessment methodologies. The IAIC shall give notice of any such changes at least 60 days prior to the date on which they shall take effect. (3) The owners of AI systems shall have the duty to provide accurate and current metadata at the time of registration and to notify the IAIC of any material changes to the registered information within: (i) 15 days of such change occurring for AI systems classified as High Risk under sub-section (4) of Section 7; (ii) 30 days of such change occurring for AI systems classified as Medium Risk under sub-section (3) of Section 7; (iii) 60 days of such change occurring for AI systems classified as Narrow Risk under sub-section (2) of Section 7; (iv) 90 days of such change occurring for AI systems classified as Narrow Risk or Medium Risk under Section 7 that are exempted from certification under sub-section (3) of Section 11. (4) Notwithstanding anything contained in sub-section (1), the owners of AI systems exempted under sub-section (3) of Section 11 shall only be required to submit the metadata specified in sub-sections (4)(i) through (4)(xi) to register their AI systems: (i) Name and version of the AI system (required) (ii) Owning entity of the AI system (required) (iii) Date of registration (required) (iv) Sector associated with the AI system (optional) (v) Specific use case(s) of the AI system (required) (vi) Technical classification of the AI system, as per Section 5 (optional) (vii)Commercial classification of the AI system as per Section 6 (required) (viii) Risk classification of the AI system as per Section 7 (required, narrow risk or medium risk only) (ix) Certification status (required) (registered & certification is exempted under sub-section (3) of Section 11) (x) Incident reporting and response protocols as per Section 19 (required) (a) Description of the incident reporting mechanisms established (e.g. hotline, online portal) (b) Timelines committed for reporting high/critical severity incidents (within 14-30 days) (c) Procedures for assessing and determining incident severity levels (only high/critical) (d) Information to be provided in incident reports (incident description, system details) (e) Confidentiality measures for incident data based on sensitivity (scaled down) (f) Minimum mitigation actions to be taken upon high/critical incident occurrence (g) Responsible personnel/team for incident response and mitigation (h) Commitments on notifying and communicating with impacted parties (i) Integration with IAIC’s central incident repository and reporting channels (j) Description of the insurance coverage obtained for the AI system, as per Section 25, including the type of policy, insurer, policy number, and coverage limits (required for high-risk AI systems only); (xi) Contact information for the owning entity (required) Illustration A small AI startup develops a chatbot for basic customer service queries using natural language processing techniques. As a low-risk AI system still in early development stages, they claim exemption under Section 11(3) and register with the following limited metadata: (i) Name and version: ChatAssist v0.5 (beta) (ii) Owning entity: XYZ AI Solutions LLP (iii) Date of registration: 15/06/2024 (iv) Sector: Not provided (optional) (v) Use case: Automated response to basic customer queries via text/voice (vi) Technical classification: Specific Purpose AI (SPAI) under Section 5(4) (optional) (vii) Commercial classification: AI-Pre under Section 6(8) (viii) Risk classification: Narrow Risk under Section 7(2) (ix) Certification status: Registered & certification exempted under Section 11(3) (x) Incident reporting protocols: · Email support@xyzai.com for incident reporting Timelines committed for reporting high/critical severity incidents (within 14-30 days) · High/critical incidents to be reported within 30 days Procedures for assessing and determining incident severity levels (only high/critical) · Only incident description and system details required Information to be provided in incident reports (incident description, system details) Confidentiality measures for incident data based on sensitivity (scaled down) · Standard data protection measures as per company policy Minimum mitigation actions to be taken upon high/critical incident occurrence · Mitigation by product team, notifying customers if major Responsible personnel/team for incident response and mitigation Commitments on notifying and communicating with impacted parties Integration with IAIC’s central incident repository and reporting channels (xi) Contact: support@xyzai.com (5) The IAIC shall put in place mechanisms to validate the metadata provided and to audit registered AI systems for compliance with the reported information. Where the IAIC determines that any developer or owner has provided false or misleading information, it may impose penalties, including fines and revocation of certification, as it deems fit. (6) The IAIC shall publish aggregate statistics and analytics based on the metadata in the National Registry for the purposes of supporting evidence-based policymaking, research, and public awareness about AI development and deployment trends. Provided that commercially sensitive information and trade secrets shall not be disclosed. (7) Registration and certification under this Act shall be voluntary, and no penal consequences shall attach to the lack of registration or certification of an AI system, except as otherwise expressly provided in this Act. (8) The examination process for registration and certification of AI use cases shall be conducted by the IAIC in a transparent and inclusive manner, engaging with relevant stakeholders, including: (i) Technical experts and researchers in the field of artificial intelligence, who can provide insights into the technical aspects, capabilities, and limitations of the AI systems under examination. (ii) Representatives of industries developing and deploying AI technologies, who can offer practical perspectives on the commercial viability, use cases, and potential impacts of the AI systems. (iii) Technology standards & business associations and consumer protection groups, who can represent the interests and concerns of end-users, affected communities, and the general public. (iv) Representatives from diverse communities and individuals who may be impacted by AI systems, to ensure their rights, needs, experiences and perspectives across different contexts are comprehensively accounted for during the examination process. (v) Any other relevant stakeholders or subject matter experts that the IAIC deems necessary for a comprehensive and inclusive examination of AI use cases. (9) The IAIC shall publish the results of its examinations for registration and certification of AI use cases, along with any recommendations for risk mitigation measures, regulatory actions, or guidelines, in an accessible format for public review and feedback. This shall include detailed explanations of the classification criteria applied, the stakeholder inputs considered, and the rationale behind the decisions made. Related Indian AI Regulation Sources Principles for Responsible AI (Part 1) February 2021 Operationalizing Principles for Responsible AI (Part 2) August 2021 Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) Committee Report August 2025 Strengthening AI Governance Through Techno-Legal Framework (White Paper, Part 2 of Emerging Policy Priorities Series) January 2026

Calcutta High Court December 2025 landmark order in IndiaMART v OpenAI finding strong prima facie case of selective algorithmic discrimination after ChatGPT excluded Indian B2B marketplace from AI-generated search results while displaying competitors, ruling USTR reports non-binding and questioning OpenAI's intermediary obligations under Indian law in India's first judicial proceeding on AI platform exclusion. IndiaMART InterMesh Limited v. OpenAI Inc. & Ors., IP-COM/57/2025 (GA-COM/1/2025), Calcutta High Court, Order dated December 24, 2025 Calcutta High Court December 2025 landmark order in IndiaMART v OpenAI finding strong prima facie case of selective algorithmic discrimination after ChatGPT excluded Indian B2B marketplace from AI-generated search results while displaying competitors, ruling USTR reports non-binding and questioning OpenAI's intermediary obligations under Indian law in India's first judicial proceeding on AI platform exclusion. Previous Next The AIACT.IN India AI Regulation Tracker 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. December 2025 Read the Document Issuing Authority Calcutta High Court (Intellectual Property Rights Division) Type of Legal / Policy Document Judicial Pronouncements - National Court Precedents Status In Force Regulatory Stage Regulatory Binding Value Legally binding instruments enforceable before courts AIACT. Regulation Visualiser Find more sources Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More Regulatory Sovereignty in India: Indigenizing Competition-Technology Approaches [ISAIL-TR-001] Learn More Deciphering Artificial Intelligence Hype and its Legal-Economic Risks [VLiGTA-TR-001] Learn More Averting Framework Fatigue in AI Governance [IPLR-IG-013] Learn More Reckoning the Viability of Safe Harbour in Technology Law, IPLR-IG-015 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

Issue-to-issue concept classification The Indic Pacific Glossary 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 Issue-to-issue concept classification Date of Addition 26 April 2024 This is one of the sub-categorised methods to classify Artificial Intelligence as a Concept, in which the conceptual framework or basis of an AI system may be recognised on an issue-to-issue basis, with unique contexts and realities. This was proposed in Artificial Intelligence Ethics and International Law (originally published in 2019). Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More An Indian Perspective on Special Purpose Acquisition Companies [GLA-TR-001] Learn More The Indic Approach to Artificial Intelligence Policy [IPLR-IG-006] Learn More Averting Framework Fatigue in AI Governance [IPLR-IG-013] 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 Previous Term Next Term

Section 9 – High-Risk AI Systems in Strategic Sectors PUBLISHED Previous Next Section 9 - High-Risk AI Systems in Strategic Sectors (1) The Central Government shall designate strategic sectors where the development, deployment, and use of high-risk AI systems shall be subject to sector-specific standards and regulations, based on the risk classification methods outlined in Chapter II of this Act. (2) In the event of any conflict between the provisions of this Act and sector-specific regulations concerning high-risk AI systems in strategic sectors, the provisions of this Act shall prevail, unless otherwise specified. Related Indian AI Regulation Sources Responsible AI #AIforAll (Discussion Paper on Facial Recognition Technology) November 2022

Karnataka's May 2025 landmark legislation establishing algorithmic transparency requirements and social security framework for platform-based gig workers. Karnataka Platform-Based Gig Workers (Social Security and Welfare) Ordinance, 2025 Karnataka's May 2025 landmark legislation establishing algorithmic transparency requirements and social security framework for platform-based gig workers. Previous Next The AIACT.IN India AI Regulation Tracker 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. May 2025 Read the Document Issuing Authority Government of Karnataka (Governor) Type of Legal / Policy Document Primary Legislation Status Enacted Regulatory Stage Regulatory Binding Value Legally binding instruments enforceable before courts AIACT. Regulation Visualiser Find more sources Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More 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 24 - Employment and Skill Security Standards Section 24 - Employment and Skill Security Standards Section 25 – Insurance Policy for AI Technologies Section 25 – Insurance Policy for AI Technologies

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. :) The Policy Purpose of a Multipolar Agenda for India, First Edition, 2023 Get this Publication 2023 ISBN 978-81-959932-4-6 Author(s) Abhivardhan Editor(s) Not Applicable IndoPacific.App Identifier (ID) IPLR-IG-001 Tags Abhivardhan, Diplomacy, Emerging Powers, Foreign Policy, Geopolitics, Global Order, India, International Relations, Multipolarity, Strategic Studies Related Terms in Techindata.in Explainers Definitions - A - E AI Knowledge Chain Accountability All-Comprehensive Approach Automation CEI Classification Class-of-Applications-by-Class-of-Application (CbC) approach Compute Ethics-based concept classification Definitions - F - J GAE Indo-Pacific International Algorithmic Law Definitions - K - P Multi-alignment Multipolar World Multipolarity Performance Effect Permeable Indigeneity in Policy (PIP) Definitions - Q - U Skirmish Propaganda Capacity Destruction Strategic Autonomy Strategic Hedging Technology Transfer Technophobia Definitions - V - Z WANA WENA 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

Rule Engine Date of Addition 26 April 2024 A rule engine is a type of software program that aids in automating decision- making processes by applying a predefined set of rules to a given dataset. It is commonly employed alongside generative AI tools to enhance the overall quality and consistency of the generated output. This was discussed in Deciphering Regulative Methods for Generative AI, VLiGTA-TR-002 (2023) . Related Long-form Insights on IndoPacific.App AI Bias & the Overlap of AI Diplomacy and Governance Ethics Dilemmas Learn More Previous Term Next Term The Indic Pacific Glossary 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

Permeable Indigeneity in Policy (PIP) Date of Addition 26 April 2024 This concept, simply means, in proposition [...] that whatsoever legal and policy changes happen, they must be reflective, and largely circumscribing of the policy realities of the country. PIP cannot be a set of predetermined cases of indigeneity in a puritan or reductionist fashion, because in both of such cases, the nuance of being manifestly unique from the very churning of policy analysis, deconstruction & understanding, is irrevocably (and maybe in some cases, not irrevocably) lost. This was proposed in Regulatory Sovereignty in India: Indigenizing Competition- Technology Approaches, ISAIL-TR-001 (2021) . Related Long-form Insights on IndoPacific.App Global Customary International Law Index: A Prologue [GLA-TR-00X] Learn More India-led Global Governance in the Indo-Pacific: Basis & Approaches [GLA-TR-003] 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 The Policy Purpose of a Multipolar Agenda for India, First Edition, 2023 Learn More The Indic Approach to Artificial Intelligence Policy [IPLR-IG-006] Learn More Reckoning the Viability of Safe Harbour in Technology Law, IPLR-IG-015 Learn More Normative Emergence in Cyber Geographies: International Algorithmic Law in a Multipolar Technological Order, First Edition Learn More Previous Term Next Term The Indic Pacific Glossary 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

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. :) Legal-Economic Issues in Indian AI Compute and Infrastructure, IPLR-IG-011 Get this Publication 2024 ISBN 978-81-977227-8-3 Author(s) Abhivardhan, Rasleen Kaur Dua Editor(s) Not Applicable IndoPacific.App Identifier (ID) IPLR-IG-011 Tags Abhivardhan, AI, AI Development, AI infrastructure, AI landscape, challenges, competition policy, compute costs, digital technology, domestic AI, economic growth, fair competition, fair play, global AI trade, global trade policies, India, Indian startups, industrial policy, Innovation, international trade policies, policy interventions, public access, public computing infrastructure, Rasleen Kaur Dua, recommendations, regulation, sector-specific agreements, small enterprises, startup ecosystem, Strategies, tech MNCs, WTO agreements Related Terms in Techindata.in Explainers Definitions - A - E applicationgiri AI as an Industry AI as a Legal Entity AI as a Subject AI as a Third Party AI Literacy AI Supply Chain AI Value Chain AI-based Anthropomorphization Accountability Algorithmic Activities and Operations Anthropomorphism-based concept classification Artificial Intelligence Hype Cycle Automation Class-of-Applications-by-Class-of-Application (CbC) approach Compute Compute Arbitrage Ethics-based concept classification Definitions - F - J 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 Token Economics Definitions - V - Z Whole-of-Government Response Related Articles in Techindata.in Insights 34 Insight(s) on AI Ethics 9 Insight(s) on AI Governance 8 Insight(s) on AI and Competition Law 8 Insight(s) on AI and Copyright Law 8 Insight(s) on AI and media sciences 8 Insight(s) on AI regulation 8 Insight(s) on AI literacy 5 Insight(s) on AI and Evidence Law 4 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

MeitY's March 2024 advisory initially requiring AI platforms to obtain government approval before deployment, later revised and superseded following industry feedback. Advisory on AI Intermediaries and Platforms MeitY's March 2024 advisory initially requiring AI platforms to obtain government approval before deployment, later revised and superseded following industry feedback. Previous Next The AIACT.IN India AI Regulation Tracker 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. March 2024 Read the Document Issuing Authority Ministry of Electronics and Information Technology (MeitY) and Ministry of Information and Broadcasting (MIB) Type of Legal / Policy Document Executive Instruments - Administrative Decisions Status Superseded Regulatory Stage Post-regulatory Binding Value Soft law (consultative) AIACT. Regulation Visualiser Find more sources Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More 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 Section 17 – Post-Deployment Monitoring of High-Risk AI Systems Section 17 – Post-Deployment Monitoring of High-Risk AI Systems