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[AIACT.IN V3] Draft Artificial Intelligence (Development & Regulation) Act, 2023, Version 3


The rapid advancement of artificial intelligence (AI) technologies necessitates a robust regulatory framework to ensure their safe and ethical deployment.


AIACT.IN, India's first privately proposed AI regulation, has been at the forefront of this effort.


Released on June 17, 2024, AIACT.IN introduces several groundbreaking features that make it a comprehensive and forward-thinking framework for AI regulation in India. You can also download AIACT.IN V3 from below.


AIACT.IN Version 3 - June 17, 2024
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In the rapidly evolving landscape of artificial intelligence (AI), the need for robust, forward-thinking regulation has never been more critical. As AI technologies continue to advance at an unprecedented pace, they bring with them both immense opportunities and significant risks. I have been been a vocal advocate for a balanced approach to AI regulation—one that harnesses the transformative potential of AI while safeguarding against its inherent risks, protecting the nascent Indian AI ecosystem.


AIACT.IN Version 3 represents a significant leap forward in this endeavour. This latest version of India's pioneering AI regulatory framework is designed to address the complexities and nuances of the AI ecosystem, ensuring that the development and deployment of AI technologies are both innovative and responsible.


Some of the notable features of AIACT.IN Version 3 include:

  1. Enhanced classification methods for AI systems, providing a more nuanced and precise evaluation of their capabilities and potential risks.

  2. The establishment of a National Registry for AI Use Cases in India, covering both untested and stable AI applications, to ensure transparency and accountability.

  3. A comprehensive approach to regulating AI-generated content, balancing the need for innovation with the protection of individual rights and societal interests.

  4. Advanced-level AI insurance policies to manage the risks associated with high-risk AI systems and ensure adequate protection for stakeholders.

  5. The introduction of AI pre-classification, enabling early assessment of potential risks and benefits.

  6. Guidance principles on AI-related contracts and corporate governance, promoting responsible AI practices within organizations.

  7. A flexible yet robust National AI Ethics Code, providing a strong ethical foundation for AI development and deployment.


This is a long read, explaining the core features of AIACT.IN Version 3 in detail.


Key Features and Improvements in AIACT.IN Version 3


Enhanced Classification Methods


  • Drastically Improved and Nuanced: The classification methods in Version 3 have been significantly enhanced to provide a more nuanced and precise evaluation of AI systems. This improvement ensures better risk management and tailored regulatory responses, addressing the diverse capabilities and potential risks associated with different AI applications.


AIACT.IN Version 3 has significantly enhanced the classification methods for AI systems, as outlined in Sections 3 to 7. These sections introduce various methods of classification, including conceptual, technical, commercial, and risk-centric approaches.

For example, Section 4 outlines the conceptual methods of classification, which consider factors such as the intended purpose, the level of human involvement, and the degree of autonomy of the AI system. This nuanced approach allows for a more precise evaluation of AI systems based on their conceptual characteristics.


Section 5 introduces technical methods of classification, which take into account the underlying algorithms, data sources, and computational resources used in the development of the AI system. This technical evaluation can help identify potential risks and tailor regulatory responses accordingly.



National Registry for AI Use Cases


  • Nuanced and Comprehensive: AIACT.IN Version 3 introduces a National Registry for AI Use Cases in India. This registry covers both untested and stable AI applications, providing a clear and organised framework for tracking AI use cases across the country. This initiative aims to standardise and certify AI applications, ensuring their safe and effective deployment.


The introduction of the National Registry for AI Use Cases in Section 12 is a significant step towards standardizing and certifying AI applications in India. This registry aims to provide a comprehensive framework for tracking both untested and stable AI use cases across the country.


For instance, the registry could include an AI-powered medical diagnostic tool that is still in the testing phase (untested AI use case) and a widely adopted AI-based chatbot for customer service (stable AI use case).


By maintaining a centralized registry, the Indian Artificial Intelligence Council (IAIC) can monitor the development and deployment of AI systems, ensuring compliance with safety and ethical standards.

Furthermore, Section 11 mandates that all AI systems operating in India must be registered with the National Registry, providing a comprehensive overview of the AI ecosystem in the country. This requirement could help identify potential risks or overlaps in AI use cases, enabling the IAIC to take proactive measures to mitigate any potential issues.


For example, if multiple organisations are developing AI-powered recruitment tools, the registry could reveal potential biases or inconsistencies in the algorithms used, prompting the IAIC to issue guidelines or standards to ensure fairness and non-discrimination in the hiring process.



Inclusive AI-Generated Content Regulation


  • Comprehensive and Balanced: The approach to regulating AI-generated content has been made more inclusive and holistic. This ensures that the diverse ways AI can create and influence content are addressed, promoting a balanced and fair regulatory environment.


Section 23 of AIACT.IN Version 3 focuses on "Content Provenance and Identification," which aims to establish a comprehensive and balanced approach to regulating AI-generated content. This section addresses the diverse ways in which AI can create and influence content, promoting a fair and inclusive regulatory environment.

Here's an example.


A news organization uses an AI system to generate articles on current events. Under Section 23, the organization would be required to clearly label these articles as "AI-generated" or provide a similar disclosure, allowing readers to understand the source of the content and make informed decisions about its credibility and potential biases.


Advanced AI Insurance Policies


  • Robust Risk Management: Version 3 introduces advanced-level AI insurance policies to better manage the risks associated with high-risk AI systems. These policies are designed to provide comprehensive coverage and protection, ensuring that stakeholders are adequately safeguarded against potential risks.


Section 25 of AIACT.IN Version 3 introduces advanced-level AI insurance policies to better manage the risks associated with high-risk AI systems. This section aims to provide comprehensive coverage and protection, ensuring that stakeholders are adequately safeguarded against potential risks.


This provision ensures that developers and deployers of high-risk AI systems maintain adequate insurance coverage to mitigate potential risks and provide compensation in case of harm or losses. Here is an example. A healthcare provider implements a high-risk AI system for medical diagnosis. Under Section 25, the provider would be required to maintain a minimum level of insurance coverage, as determined by the IAIC, to protect patients and the healthcare system from potential harm or losses resulting from errors or biases in the AI system's diagnoses.


AI-Pre Classification


  • Early Risk and Benefit Assessment: The concept of AI pre-classification has been introduced to help stakeholders understand potential risks and benefits early in the development process. This proactive approach allows for better planning and risk mitigation strategies.


Section 6(8) of the Draft Artificial Intelligence (Development & Regulation) Act, 2023, introduces the classification method known as "Artificial Intelligence for Preview" (AI-Pre). This classification pertains to AI technologies that are made available by companies for testing, experimentation, or early access prior to their wider commercial release. AI-Pre encompasses AI products, services, components, systems, platforms, and infrastructure at various stages of development.

The key characteristics of AI-Pre technologies include:

  1. Limited Access: The AI technology is made available to a limited set of end-users or participants in a preview program.

  2. Special Agreements: Access to the AI-Pre technology is subject to special agreements that govern usage terms, data handling, intellectual property rights, and confidentiality.

  3. Development Stage: The AI technology may not be fully tested, documented, or supported, and the company providing it may offer no warranties or guarantees regarding its performance or fitness for any particular purpose.

  4. User Feedback: Users of the AI-Pre technology are often expected to provide feedback, report issues, or share data to help the company refine and improve the technology.

  5. Cost and Pricing: The AI-Pre technology may be provided free of charge or under a separate pricing model from the company’s standard commercial offerings.

  6. Post-Preview Release: After the preview period concludes, the company may release a commercial version of the AI technology, incorporating improvements and modifications based on feedback and data gathered during the preview. Alternatively, the company may choose not to proceed with a commercial release.

Here's an illustration.


A technology company develops a new general-purpose AI system that can engage in open-ended dialogue, answer questions, and assist with tasks across a wide range of domains. The company makes a preview version of the AI system available to select academic and industry partners with the following characteristics:

  • The preview is accessible to the partners via an API, subject to a special preview agreement that governs usage terms, data handling, and confidentiality.

  • The AI system’s capabilities are not yet fully tested, documented, or supported, and the company provides no warranties or guarantees.

  • The partners can experiment with the system, provide feedback to the company to help refine the technology, and explore potential applications.

  • After the preview period, the company may release a commercial version of the AI system as a paid product or service, with expanded capabilities, service level guarantees, and standard commercial terms.


Importance for AI Regulation in India


The AI-Pre classification method is significant for AI regulation in India for several reasons:

  1. Innovation and Experimentation: AI-Pre allows companies to innovate and experiment with new AI technologies in a controlled environment. This fosters creativity and the development of cutting-edge AI solutions without the immediate pressure of full commercial deployment.

  2. Risk Mitigation: By classifying AI technologies as AI-Pre, companies can identify and address potential risks, technical issues, and ethical concerns during the preview phase. This helps in mitigating risks before the technology is widely released.

  3. Feedback and Improvement: The feedback loop created by AI-Pre enables companies to gather valuable insights from early users. This feedback is crucial for refining the technology, improving its performance, and ensuring it meets user needs and regulatory standards.

  4. Regulatory Compliance: AI-Pre provides a framework for companies to comply with regulatory requirements while still in the development phase. This ensures that AI technologies are developed in line with legal and ethical standards from the outset.

  5. Market Readiness: The AI-Pre classification helps companies gauge market readiness and demand for their AI technologies. It allows them to make informed decisions about the commercial viability and potential success of their products.

  6. Transparency and Accountability: The special agreements and documentation required for AI-Pre technologies promote transparency and accountability. Companies must clearly outline the terms of use, data handling practices, and intellectual property rights, ensuring that all stakeholders are aware of their responsibilities and rights.


Guidance Principles on AI-Related Contracts


  • Clarity and Adoption: A whole new approach to guidance principles on AI-related contracts has been introduced. These principles ensure that agreements involving AI are clear, fair, and aligned with best practices, fostering trust and transparency in AI transactions.


AIACT.IN Version 3 introduces a comprehensive approach to guidance principles on AI-related contracts in Section 15. These principles ensure that agreements involving AI are clear, fair, and aligned with best practices, fostering trust and transparency in AI transactions.


Consider a scenario where a healthcare provider enters into a contract with an AI company to implement an AI-based diagnostic tool. Under the guidance principles outlined in Section 15, the contract would need to include clear provisions regarding the responsibilities of both parties, the transparency of the AI system's decision-making process, and the accountability mechanisms in place in case of errors or biases in the AI's diagnoses. This would ensure that the healthcare provider and the AI company have a mutual understanding of their roles and responsibilities, fostering trust and reducing the risk of disputes.


Here are some other features of AIACT.IN Version 3 described in brief:


AI and Corporate Governance


  • Ethical Practices: New guidance principles around AI and corporate governance emphasize the importance of ethical AI practices within corporate structures. This promotes responsible AI use at the organizational level, ensuring accountability and transparency.


National AI Ethics Code


  • Flexible and Non-Binding: The National AI Ethics Code introduced in Version 3 is non-binding yet flexible, providing a strong ethical foundation for AI development and deployment. This code encourages adherence to high ethical standards without stifling innovation.