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Omnipotence Date of Addition 26 April 2024 In the context of Artificial Intelligence, this implies that any AI system, due to its inherent yet limited features of processing and generating outputs, could be effective in shaping multiple sectors, eventualities and legal dilemmas. In short, any omnipotent AI system could have first, second & third order effects due to its actions. This was discussed in Artificial Intelligence Ethics and International Law (originally published in 2019), Regulatory Sovereignty in India: Indigenizing Competition- Technology Approaches, ISAIL-TR-001 (2021), Deciphering Regulative Methods for Generative AI, VLiGTA-TR-002 (2023) and many key publications by ISAIL & VLiGTA . Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More 2021 Handbook on AI and International Law [RHB 2021 ISAIL] Learn More Draft Digital Competition Bill, 2024 for India: Feedback Report [IPLR-IG-003] 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 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 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 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

Performance Effect Date of Addition 22 March 2025 A phenomenon identified in compute efficiency research where, over time, a given level of compute investment enables increased model performance due to improvements in algorithms, hardware, and training methods. According to the Arxiv paper "Increased Compute Efficiency and the Diffusion of AI Capabilities," there are two key effects of improving compute efficiency: (1) the performance effect, where technical institutions and AI companies achieve better results with the same compute investment over time; and (2) the access effect, where achieving a specific performance level requires less compute investment as time passes. Together, these effects mean that while AI capabilities become more accessible to smaller players over time, large compute investors can maintain their leading position by pioneering new capabilities. Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More The Policy Purpose of a Multipolar Agenda for India, First Edition, 2023 Learn More Draft Digital Competition Bill, 2024 for India: Feedback Report [IPLR-IG-003] Learn More Reimaging and Restructuring MeiTY for India [IPLR-IG-007] 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 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

Phenomena-based 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, beyond technical and ethical questions, it is possible that AI systems may render purpose based on natural and human-related phenomena. This idea was discussed 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 2021 Handbook on AI and International Law [RHB 2021 ISAIL] Learn More 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 Draft Digital Competition Bill, 2024 for India: Feedback Report [IPLR-IG-003] 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 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 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

Delhi High Court September 2025 interim injunction restraining unauthorized commercial exploitation of actor Abhishek Bachchan's personality rights. Abhishek Bachchan v. The Bollywood Tee Shop & Ors., CS(COMM) 960/2025, Delhi High Court, Order dated September 10, 2025 Delhi High Court September 2025 interim injunction restraining unauthorized commercial exploitation of actor Abhishek Bachchan's personality rights. 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. September 2025 Read the Document 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 AIACT. Regulation Visualiser Find more sources 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

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

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 The LegalTechPolicy.com Playbook, First Edition Learn More 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 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. :) [Version 2] Draft Artificial Intelligence (Development & Regulation) Act, 2023 Get this Publication 2024 ISBN Not Applicable Author(s) Abhivardhan, Akash Manwani Editor(s) Not Applicable IndoPacific.App Identifier (ID) AIACT2 Tags Not Applicable Related Terms in Techindata.in Explainers Definitions - A - E AI as a Concept AI as an Object AI as a Subject AI as a Third Party Accountability Definitions - F - J Framework Fatigue 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 a collection of standalone use cases related to one another (GAI2) Intended Purpose / Specified Purpose Definitions - K - P Manifest Availability Multivariant, Fungible & Disruptive Use Cases & Test Cases of Generative AI Parameters Privacy by Default Privacy by Design Proprietary Information Definitions - Q - U SOTP Classification Technology Transfer Transformer Model 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 regulation 8 Insight(s) on AI literacy 4 Insight(s) on Abhivardhan 4 Insight(s) on AIACT.in . Previous Item Next Item

Language Model Date of Addition 22 March 2025 An AI algorithm that uses deep learning techniques and large datasets to understand, summarise, generate, and predict text-based content. Large language models (LLMs) dramatically expand this capability through transformer architectures and massive parameter counts. Modern language models, particularly LLMs, are trained on vast corpora of text data through multiple training stages, typically starting with unsupervised learning on unstructured data followed by fine-tuning with self-supervised learning. They employ transformer neural networks with self-attention mechanisms to understand relationships between words and concepts. This architecture enables them to assign weights to different tokens to determine contextual relationships. Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] 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 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 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 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 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 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 22 – Shared Sector-Neutral & Sector-Specific Standards PUBLISHED Previous Next Section 22 - Shared Sector-Neutral & Sector-Specific Standards (1) The IAIC shall coordinate the implementation and review of the following sector-neutral standards for the responsible development, deployment, and use of AI systems: (i) Fundamental Principles of Liability as outlined in sub-sections (2), (3), and (4); (2) Liability for harm or damage caused by an AI system shall be allocated based on the following principles: (i) The party that developed, deployed, or operated the AI system shall be primarily liable for any harm or damage caused by the system, taking into account the system’s classification under the conceptual, technical, commercial, and risk-based methods. (ii) Liability may be shared among multiple parties involved in the AI system’s lifecycle, based on their respective roles and responsibilities, as well as the system’s classification and associated requirements under Sections 8 and 9. (iii) End-users shall not be held liable for harm or damage caused by an AI system, unless they intentionally misused or tampered with the system, or failed to comply with user obligations specified based on the system’s classification. (3) To determine and adjudicate liability for harm caused by AI systems, the following factors shall be considered: (i) The foreseeability of the harm, in light of the AI system’s intended purpose as identified by the Issue-to-Issue Concept Classification (IICC) under Section 4(2), its capabilities as specified in the Technical Classification under Section 5, and its limitations according to the Risk Classification under Section 7; (ii) The degree of control exercised over the AI system, considering the human oversight and accountability requirements tied to its Risk Classification under Section 7, particularly the principles of Human Agency and Oversight as outlined in Section 13; (4) Developers and operators of AI systems shall be required to obtain liability insurance to cover potential harm or damage caused by their AI systems. The insurance coverage shall be proportionate to the risk levels and potential impacts of the AI systems, as determined under the Risk Classification framework in Section 7, and the associated requirements for high-risk AI systems outlined in Section 9. This insurance policy shall ensure that compensation is available to affected individuals or entities in cases where liability cannot be attributed to a specific party. (5) The IAIC shall enable coordination among sector-specific regulators for the responsible development, deployment, and use of AI systems in sector-specific contexts based on the following set of principles: (i) Transparency and Explainability: (a) AI systems should be designed and developed in a transparent manner, allowing users to understand how they work and how decisions are made. (b) AI systems should be able to explain their decisions in a clear and concise manner, allowing users to understand the reasoning behind their outputs. (c) Developers should provide clear documentation and user guides explaining the AI system’s capabilities, limitations, and potential risks. (d) The level of transparency and explainability required may vary based on the AI system’s risk classification and intended use case. (ii) Fairness and Bias: (a) AI systems should be regularly monitored for technical bias and discrimination, and appropriate mitigation measures should be implemented to address any identified issues in a sociotechnical context. (b) Developers should ensure that training data is diverse, representative, and free from biases that could lead to discriminatory outcomes. (c) Ongoing audits and assessments should be conducted to identify and rectify any emerging biases during the AI system’s lifecycle. (iii) Safety and Security: (a) AI systems should be designed and developed with safety and security by design & default. (b) AI systems should be protected from unauthorized access, modification, or destruction. (c) Developers should implement robust security measures, such as encryption, access controls, and secure communication protocols, to safeguard AI systems and their data. (d) AI systems should undergo rigorous testing and validation to ensure they perform safely and reliably under normal and unexpected conditions. (e) Developers should establish incident response plans and mechanisms to promptly address any safety or security breaches. (iv) Human Control and Oversight: (a) AI systems should be subject to human control and oversight to ensure that they are used responsibly. (b) There should be mechanisms in place for data principals to intervene in the operation of AI systems if necessary. (c) Developers should implement human-in-the-loop or human-on-the-loop approaches, allowing for human intervention and final decision-making in critical or high-risk scenarios. (d) Clear protocols should be established for escalating decisions to human operators when AI systems encounter situations beyond their designed scope or when unexpected outcomes occur. (e) Regular human audits and reviews should be conducted to ensure AI systems are functioning as intended and aligned with human values and societal norms. (iv) Open Source and Interoperability: (a) The development of shared sector-neutral standards for AI systems shall leverage open source software and open standards to promote interoperability, transparency, and collaboration. (b) The IAIC shall encourage the participation of open source communities and stakeholders in the development of AI standards. (c) Developers should strive to use open source components and frameworks when building AI systems to facilitate transparency, reusability, and innovation. (d) AI systems should be designed with interoperability in mind, adhering to common data formats, protocols, and APIs to enable seamless integration and data exchange across different platforms and domains. (e) The IAIC shall promote the development of open benchmarks, datasets, and evaluation frameworks to assess and compare the performance of AI systems transparently. Related Indian AI Regulation Sources Reporting for Artificial Intelligence (AI) and Machine Learning (ML) applications and systems offered and used by market participants January 2019 Tamil Nadu Safe and Ethical Artificial Intelligence Policy 2020 October 2020 The Ethical Guidelines for Application of AI in Biomedical Research and Healthcare March 2023 Fairness Assessment and Rating of Artificial Intelligence Systems (TEC 57050:2023) July 2023 Technical Guidelines on SBOM, QBOM & CBOM, AIBOM, HBOM (Version 2.0) July 2025

Object-Oriented Design Date of Addition 26 April 2024 Object-oriented design (OOD) is a software design methodology that organizes software around data, or objects, rather than functions and logic. This was discussed in Deciphering Regulative Methods for Generative AI, VLiGTA-TR-002 (2023) . Related Long-form Insights on IndoPacific.App The LegalTechPolicy.com Playbook, First Edition Learn More Regularizing Artificial Intelligence Ethics in the Indo-Pacific [GLA-TR-002] Learn More Regulatory Sandboxes for Artificial Intelligence: Techno-Legal Approaches for India [ISAIL-TR-002] 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 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 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 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 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 30 – Power to Make Regulations PUBLISHED Previous Next Section 30 - Power to Make Regulations (1) The IAIC may, by notification, make regulations consistent with this Act and the rules made thereunder to carry out the provisions of this Act. (2) In particular, and without prejudice to the generality of the foregoing power, such regulations may provide for all or any of the following matters, namely — (a) The criteria and process for the classification of AI systems based on their conceptual, technical, commercial, and risk-based factors, as specified in Sections 4, 5, 6, and 7; (b) The standards, guidelines, and best practices for the development, deployment, and use of AI systems, including those related to transparency, explainability, fairness, safety, security, and human oversight, as outlined in Section 13; (c) The procedures and requirements for the registration and certification of AI systems, including the criteria for exemptions and the maintenance of the National Registry of Artificial Intelligence Use Cases, as specified in Sections 11 and 12; (d) The guidelines and mechanisms for post-deployment monitoring of high-risk AI systems, as outlined in Section 17; (e) The procedures and protocols for third-party vulnerability reporting, incident reporting, and responsible information sharing, as mentioned in Sections 18, 19, and 20; (f) The guidelines and requirements for content provenance and identification in AI-generated content, as specified in Section 23; (g) The insurance coverage requirements and risk assessment procedures for entities developing or deploying high-risk AI systems, as outlined in Section 25; (h) Any other matter which is required to be, or may be, prescribed, or in respect of which provision is to be made by regulations. (3) Every regulation made under this Act shall be laid, as soon as may be after it is made, before each House of Parliament, while it is in session, for a total period of thirty days which may be comprised in one session or in two or more successive sessions, and if, before the expiry of the session immediately following the session or the successive sessions aforesaid, both Houses agree in making any modification in the regulation or both Houses agree that the regulation should not be made, the regulation shall thereafter have effect only in such modified form or be of no effect, as the case may be; so, however, that any such modification or annulment shall be without prejudice to the validity of anything previously done under that regulation. Related Indian AI Regulation Sources

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. :) Artificial Intelligence and Policy in India, Volume 5 [AIPI-V5] Get this Publication 2024 ISBN 978-81-959932-6-0 Author(s) Bhavya Singh, Harinandana V, Purnima Sihmar Editor(s) Abhivardhan, Pratejas Tomar IndoPacific.App Identifier (ID) AIPI-V5 Tags Accountability, AI and agriculture, AI and climate change, AI and cybersecurity, AI and defense, AI and democracy, AI and developing countries, AI and discrimination, AI and e-commerce, AI and education, AI and employment, AI and energy, AI and existential risk, AI and finance, AI and healthcare, AI and human rights, AI and intellectual property, AI and international relations, AI and law enforcement, AI and manufacturing, AI and national security, AI and smart cities, AI and social media, AI and supply chain, AI and surveillance, AI and sustainability, AI and the future of work, AI and the meaning of life., AI and the singularity, AI and transportation, AI applications, AI governance frameworks, AI policy, AI safety, algorithmic bias, Artificial Intelligence, autonomous systems, computer vision, data privacy, deep learning, Ethics, Explainable AI, Governance, Machine Learning, natural language processing, Pratejas Tomar, regulation, Responsible AI, robotics, society, Transparency, trustworthy AI Related Terms in Techindata.in Explainers Definitions - A - E AI as an Entity AI as an Industry AI Explainability Clause AI-based Anthropomorphization Accountability Algorithmic Activities and Operations 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 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