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Neurosymbolic AI Date of Addition 22 March 2025 An advanced AI approach that integrates neural networks (for pattern recognition) with symbolic reasoning (rule-based logical processing). This hybrid architecture aims to combine the learning capabilities of deep learning with the interpretability and reasoning abilities of symbolic AI. Neurosymbolic AI systems consist of multiple components working in harmony: a neural network for perception tasks, a symbolic reasoning engine for applying logical rules, an integration layer connecting these components, a knowledge base storing structured information, an explanation generator for transparency, and a user interface for human interaction. This approach offers advantages in explainability, accuracy, context understanding, flexibility, and complex problem-solving. Real-world applications include financial fraud detection, customer support systems, supply chain optimization, and environmental monitoring. Related Long-form Insights on IndoPacific.App Averting Framework Fatigue in AI Governance [IPLR-IG-013] Learn More Normative Emergence in Cyber Geographies: International Algorithmic Law in a Multipolar Technological Order, First Edition 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

Accountability Explainers The Complete Glossary Accountability Date of Addition 22 Mar 2025 The responsibility of AI developers, organizations, and stakeholders to ensure AI systems operate ethically, legally, and transparently. It involves mechanisms that enable AI decision-making to be monitored, explained, and challenged when necessary. Accountability in AI can be categorised into several types: procedural accountability (ensuring transparent development processes), operational accountability (focusing on system performance and outcomes), ethical accountability (aligning AI with ethical norms), and legal accountability (complying with relevant regulations). In automated decision-making contexts, accountability ensures decisions are justified and transparent. Related Long-form Insights on IndoPacific.App 2021 Handbook on AI and International Law [RHB 2021 ISAIL] Learn More Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] Learn More An Indian Perspective on Special Purpose Acquisition Companies [GLA-TR-001] Learn More Regulatory Sovereignty in India: Indigenizing Competition-Technology Approaches [ISAIL-TR-001] Learn More Regulatory Sandboxes for Artificial Intelligence: Techno-Legal Approaches for India [ISAIL-TR-002] 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 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 [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 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 [AIACT.IN V3] Draft Artificial Intelligence (Development & Regulation) Act, 2023, Version 3 Learn More AIACT.IN Version 3 Quick Explainer Learn More The Indic Approach to Artificial Intelligence Policy [IPLR-IG-006] Learn More Reimaging and Restructuring MeiTY for India [IPLR-IG-007] Learn More Artificial Intelligence and Policy in India, Volume 5 [AIPI-V5] 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 Sections 4-9, AiACT.IN V4 Infographic Explainers Learn More Decoding the AI Competency Triad for Public Officials [IPLR-IG-014] 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 The Global AI Inventorship Handbook, First Edition [RHB-AI-INVENT-001-2025] 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 2020 Handbook on AI and International Law [RHB 2020 ISAIL] 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

Technology by Design Date of Addition 26 April 2024 This refers to the deliberate use of AI technology to achieve specific goals. For example, a company might design an AI system to help them identify and recruit the best candidates for a job. 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 Regulatory Sandboxes for Artificial Intelligence: Techno-Legal Approaches for India [ISAIL-TR-002] 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 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 Reimaging and Restructuring MeiTY for India [IPLR-IG-007] Learn More Artificial Intelligence and Policy in India, Volume 5 [AIPI-V5] 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 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 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

MeitY's March 2024 advisory initially requiring AI platforms to obtain government approval before deployment, later revised and superseded following industry feedback. 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 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 March 2024 Issuing Authority Ministry of Electronics and Information Technology (MeitY) Type of Legal / Policy Document Executive Instruments - Administrative Decisions Status Superseded Regulatory Stage Post-regulatory Binding Value Soft law (consultative) 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 Section 17 – Post-Deployment Monitoring of High-Risk AI Systems Section 17 – Post-Deployment Monitoring of High-Risk AI Systems

GaryMarcus'd 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 GaryMarcus'd Date of Addition 7 June 2025 To "GaryMarcus'd" is a colloquial verb derived from the name of cognitive scientist Gary Marcus, referring to the act of critically exposing or debunking the overhyped capabilities of artificial intelligence (AI), particularly large language models (LLMs), by highlighting their limitations in reasoning, understanding, or general intelligence. It implies a rigorous, often public critique that challenges the narrative of AI as a near-human or AGI-level system, emphasising its reliance on pattern matching rather than true cognitive processes. Context : The term originates from Marcus's long-standing skepticism toward deep learning and LLMs, as seen in his debates on X and publications like his 2022 Nature paper. The post by Josh Wolfe (@wolfejosh) on June 7, 2025, uses "Apple just GaryMarcus'd LLM reasoning ability" to suggest that Apple's study mirrors Marcus's critique, revealing LLMs' collapse under complex reasoning tasks. Indic Language Translations and Nuances Hindi: "गैरीमार्कस्ड" (GairīMārkasḍ) – Implies a scholarly takedown or exposure of AI flaws, with "मार्कस" (Mārkas) adapted from Marcus and "ड" (ḍ) adding a past-tense flavour to indicate the action is complete. In an Indic context, this term could resonate with the philosophical tradition of questioning artificial constructs (e.g., Maya in Hindu thought) versus true intelligence, aligning with Marcus's call for symbolic AI to complement statistical methods. Related Long-form Insights on IndoPacific.App Deciphering Artificial Intelligence Hype and its Legal-Economic Risks [VLiGTA-TR-001] Learn More Normative Emergence in Cyber Geographies: International Algorithmic Law in a Multipolar Technological Order, First Edition Learn More Previous Term Next Term

Inference Latency 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 Inference Latency Date of Addition 17 October 2025 The time delay measured in milliseconds between submitting a query to an AI model and receiving the complete generated response, representing a critical performance metric that directly impacts user experience in production applications. Inference latency comprises multiple components including network transmission time, request queuing, prompt processing, iterative token generation, and response formatting, with each element subject to optimization through architectural choices and infrastructure configuration. High latency undermines real-time conversational interfaces, chatbots, and interactive applications where users expect sub-second response times, making it a primary constraint determining which model architectures and deployment strategies are viable for specific use cases regardless of accuracy advantages. Related Long-form Insights on IndoPacific.App Auditing AI Companies for Corporate Internal Investigations in India, VLiGTA-TR-005 Learn More Artificial Intelligence Governance using Complex Adaptivity: Feedback Report, First Edition, 2024 Learn More NIST Adversarial Machine Learning Taxonomies: Decoded, IPLR-IG-016 Learn More Previous Term Next Term

Compute Arbitrage Explainers The Complete Glossary Compute Arbitrage Date of Addition 17 Oct 2025 An economic strategy that exploits geographic, temporal, or market-based pricing differentials in GPU compute resources to reduce costs for AI model training and inference workloads. This practice involves dynamically shifting computational tasks across cloud regions with lower electricity rates, opportunistically utilizing spot instances during off-peak hours, or leveraging jurisdictional variations in data center operational expenses. Compute arbitrage has emerged as a critical cost optimization discipline for AI companies as training expenses for frontier models reach tens of millions of dollars, with sophisticated operators achieving 30-50% cost reductions through strategic resource allocation across heterogeneous infrastructure providers. Related Long-form Insights on IndoPacific.App Artificial Intelligence Governance using Complex Adaptivity: Feedback Report, First Edition, 2024 Learn More Legal-Economic Issues in Indian AI Compute and Infrastructure, IPLR-IG-011 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

Benchmark Gaming Explainers The Complete Glossary Benchmark Gaming Date of Addition 17 Oct 2025 The practice of optimizing AI models specifically for standardized evaluation metrics and leaderboard performance rather than genuine real-world capability or generalization. This phenomenon occurs when development teams tune hyperparameters, training data, or architectural choices to maximize scores on popular benchmarks while potentially degrading performance on practical applications not represented in test sets. Benchmark gaming undermines the validity of AI progress measurements by creating a disconnect between reported achievements and actual system utility, contributing to AI hype cycles and misaligned research incentives that prioritize metric manipulation over substantive technical advancement. Related Long-form Insights on IndoPacific.App Averting Framework Fatigue in AI Governance [IPLR-IG-013] Learn More Indo-Pacific Research Ethics Framework on Artificial Intelligence Use [IPac AI] 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

Small Language Models Date of Addition 17 October 2025 Compact neural network architectures typically containing fewer than 10 billion parameters that are optimized for specific domains, tasks, or deployment constraints rather than pursuing general-purpose capabilities. The emergence of SLMs reflects industry recognition that scaling alone does not solve fundamental AI challenges and that efficiency-optimized models better serve enterprise production requirements. Related Long-form Insights on IndoPacific.App 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 Decoding the AI Competency Triad for Public Officials [IPLR-IG-014] 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

Delhi High Court December 2019 landmark judgment on software patentability under Section 3(k) of Patents Act establishing "technical effect" test for computer-related inventions. 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. Ferid Allani v. Union of India & Ors., W.P.(C) 7/2014 (Delhi High Court, Dec 12, 2019) Delhi High Court December 2019 landmark judgment on software patentability under Section 3(k) of Patents Act establishing "technical effect" test for computer-related inventions. Previous Next December 2019 Issuing Authority Delhi High Court, IPAB Type of Legal / Policy Document Judicial Pronouncements - National Court Precedents Status Enacted 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 The Global AI Inventorship Handbook, First Edition [RHB-AI-INVENT-001-2025] Learn More Related draft AI Law Provisions of aiact.in Section 3 – Classification of Artificial Intelligence Section 3 – Classification of Artificial Intelligence Section 7 – Risk-centric Methods of Classification Section 7 – Risk-centric Methods of Classification Section 8 – Prohibition of Unintended Risk AI Systems Section 8 – Prohibition of Unintended Risk AI Systems

AI Knowledge Chain Explainers The Complete Glossary AI Knowledge Chain Date of Addition 5 Mar 2025 A structured sequence of information transformation processes that enable AI systems to convert raw data into actionable insights through interconnected stages of knowledge acquisition, representation, reasoning, and application. Knowledge chains encompass both the technical pathways within AI systems and the human-AI information exchanges that facilitate meaningful interpretation of AI outputs. Robust knowledge chains maintain logical coherence between information elements while providing transparent connections between premises and conclusions. Related Long-form Insights on IndoPacific.App 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 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 The Legal and Ethical Implications of Monosemanticity in LLMs [IPLR-IG-008] 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 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

Section 10 – Composition and Functions of the Council PUBLISHED Previous Next Section 10 - Composition and Functions of the Council (1) With effect from the date notified by the Central Government, there shall be established the Indian Artificial Intelligence Council (IAIC), a statutory body for the purposes of this Act. (2) The IAIC shall be an autonomous body corporate with perpetual succession, a common seal, and the power to acquire, hold and transfer property, both movable and immovable, and to contract and be contracted, and sue or be sued by its name. (3) The IAIC shall coordinate and oversee the development, deployment, and governance of artificial intelligence systems across all government bodies, ministries, departments, and regulatory authorities, adopting a whole-of-government approach. (4) The headquarters of the IAIC shall be located at the place notified by the Central Government. (5) The IAIC shall consist of a Chairperson and such number of other Members, not exceeding [X], as the Central Government may notify. (6) The Chairperson and Members shall be appointed by the Central Government through a transparent and merit-based selection process, as may be prescribed. (7) The Chairperson and Members shall be individuals of eminence, integrity and standing, possessing specialized knowledge or practical experience in fields relevant to the IAIC’s functions, including but not limited to: (i) Data and artificial intelligence governance, policy and regulation; (ii) Administration or implementation of laws related to consumer protection, digital rights and artificial intelligence and other emerging technologies; (iii) Dispute resolution, particularly technology and data-related disputes; (iv) Information and communication technology, digital economy and disruptive technologies; (v) Law, regulation or techno-regulation focused on artificial intelligence, data protection and related domains; (vi) Any other relevant field deemed beneficial by the Central Government. (8) At least three Members shall be experts in law with demonstrated understanding of legal and regulatory frameworks related to artificial intelligence, data protection and emerging technologies. (9) The IAIC shall have the following functions: (i) Develop and implement policies, guidelines and standards for responsible development, deployment and governance of AI systems in India; (ii) Coordinate and collaborate with relevant ministries, regulatory bodies and stakeholders to ensure harmonised AI governance across sectors; (iii) Establish and maintain the National Registry of AI Use Cases as per Section 12; (iv) Administer the certification scheme for AI systems as specified in Section 11; (v) Develop and promote the National AI Ethics Code as outlined in Section 13; (vi) Facilitate stakeholder consultations, public discourse and awareness on societal implications of AI; (vii) Promote research, development and innovation in AI with a focus on responsibility and ethics; (viii) Engage with international AI regulatory bodies, standard-setting organizations, and global AI safety initiatives to promote knowledge exchange and align India’s AI governance framework with global best practices. This includes: (a) Developing bilateral and multilateral agreements to support collaborative research, data sharing, and risk management. (b) Participating in international AI safety and ethics dialogues to shape global AI norms. (c) Coordinating on cross-border data flow standards and AI certification criteria to ensure seamless compliance for international AI applications in India. (ix) Take regulatory actions to ensure compliance with the policies, standards, and guidelines issued by the IAIC under this Act, which may include: (a) Issuing show-cause notices requiring non-compliant entities to explain the reasons for non-compliance and outline corrective measures within a specified timeline; (b) Imposing monetary penalties based on the severity of non-compliance, the risk level involved, and the potential impact on individuals, businesses, or society, with penalties being commensurate with the financial capacity of the non-compliant entity; (c) Suspending or revoking certifications, registrations, or approvals related to non-compliant AI systems, preventing their further development, deployment, or operation until compliance is achieved; (d) Mandating independent audits of the non-compliant entity’s processes at their own cost, with audit reports to be submitted to the IAIC for review and further action; (e) Issuing directives to non-compliant entities to implement specific remedial measures within a defined timeline, such as enhancing data quality controls, improving governance frameworks, or strengthening decision-making procedures; (f) In cases of persistent or egregious non-compliance, recommending the temporary or permanent suspension of the non-compliant entity’s AI-related operations, subject to due process and the principles of natural justice; (g) Taking any other regulatory action deemed necessary and proportionate to ensure compliance with the prescribed standards and to safeguard the responsible development, deployment, and use of AI systems. (x) Advise the Central Government on matters related to AI policy, regulation and governance, and recommend legislative or regulatory changes as necessary; (xi) Perform any other functions necessary to achieve the objectives of this Act or as assigned by the Central Government. (10)The IAIC may constitute advisory committees, expert groups or task forces as deemed necessary to assist in its functions. (11)The IAIC shall endeavour to function as a digital office to the extent practicable, conducting proceedings, filings, hearings and pronouncements through digital means as per applicable laws. Related Indian AI Regulation Sources Report on AI Governance Guidelines Development January 2025 Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) Committee Report August 2025 India AI Governance Guidelines: Enabling Safe and Trusted AI Innovation November 2025 Digital Personal Data Protection Rules, 2025 November 2025