Indic Pacific Legal Research

Chapter V: KNOWLEDGE MANAGEMENT AND DECISION-MAKING

Section 14 - Model Standards on Knowledge Management

(1)   The IAIC shall develop, document and promote comprehensive model standards on knowledge management practices concerning the development, maintenance, and governance of high-risk AI systems. These standards shall focus on the effective management of knowledge assets;

(2)   The model standards shall encompass the following areas:

(i)    Intellectual property management practices to safeguard and leverage AI-related intellectual property rights such as patents, copyrights, trademarks and industrial designs.

(ii)   Processes for documenting and organizing technical knowledge assets like research reports, manuals, standards and industrial practices related to AI systems.

(iii) Frameworks for capturing, retaining and transferring the tacit knowledge and expertise of human capital involved in AI development and deployment.

(iv)  Organisational systems and methodologies to enable effective knowledge capture, storage, retrieval and utilisation across the AI system lifecycle.

(v)   Mechanisms for leveraging customer-related knowledge assets such as data, feedback and insights to enhance AI system development and performance.

(vi)  Analytical techniques to derive knowledge from data analysis, including identifying patterns, trends and developing predictive models for AI systems.

(vii)Collaborative practices to foster cross-functional knowledge sharing and generation through teams, communities of practice and other initiatives.

(3)   All entities engaged in the development, deployment, or utilisation of high-risk AI systems shall be bound by the model standards on knowledge management and decision-making as provided by this section. The compliance timeline for such high-risk AI systems shall be determined by the IAIC and may vary based on the technical, commercial and risk-based classification of those systems under Section 12.

(4)   The Central Government shall empower the IAIC or agencies to establish a knowledge management registry process to enable the standardisation of various knowledge management practices and procedures associated with the life cycle of AI systems.

(5)   The entities responsible for the development of high-risk AI systems shall be required to submit regular audit reports to the IAIC, outlining their adherence to the model standards for knowledge management and decision-making.

(6)   For artificial intelligence technologies subject to commercial classification as determined by the factors outlined in sub-section (1) of Section 6, the requirement to comply with these model standards on knowledge management shall be assessed by the IAIC on a case-by-case basis, taking into consideration the specific commercial classification factors applicable to each AI technology.

Illustration

A startup has developed an AI-powered language translation app that allows users to translate text, documents, and speech between multiple Indian languages. Based on an assessment of the factors in Section 6(1), such as the app’s user base, market influence, and data integration, the IAIC may determine that this AI technology falls under the AI-Pro or AIaaS category. The IAIC will then evaluate if the startup needs to fully comply with the knowledge management standards or if certain requirements can be relaxed or made optional based on the app’s specific use case and commercial profile.

(7)   In determining the case-by-case application of these model standards to commercially classified AI technologies under sub-section (1) of Section 6, the IAIC shall take into account any relevant sector-specific standards, codes of practice, or regulatory guidelines pertaining to knowledge management practices in the sector to which the AI technology belongs or is intended to be deployed.

Illustration

An agritech startup has developed an AI system that analyzes satellite imagery and weather data to provide crop yield predictions and advisory services to farmers. As this AI technology falls within the agriculture sector, the IAIC’s assessment of its knowledge management requirements will consider any relevant guidelines or standards issued by bodies like the Indian Council of Agricultural Research (ICAR) or the Ministry of Agriculture & Farmers’ Welfare. These may include data governance norms for agricultural data, model validation protocols for AI-based advisory services, or best practices for maintaining data trails and audit logs in agritech applications.

(8)   Failure to adhere to the prescribed model standards for knowledge management and decision-making processes shall result in regulatory actions by the IAIC, which may include:

(i)    Issuance of show-cause notices to the non-compliant entity, requiring them to explain the reasons for non-compliance and outline corrective measures within a specified timeline.

(ii)   Imposition of monetary penalties, determined based on the severity of non-compliance, the risk level of the AI system involved, and the potential impact on individuals, businesses, or society. The monetary penalties shall be commensurate with the financial capacity of the non-compliant entity.

(iii) Suspension or revocation of certifications or registrations related to the non-compliant AI system, preventing its further development, deployment, or operation until compliance is achieved.

(iv)  Mandating independent audits of the non-compliant entity’s knowledge management and decision-making processes at their own cost, with the audit reports to be submitted to the IAIC for review and further action.

(v)   Issuing directives to the non-compliant entity to implement specific remedial measures, such as enhancing data quality controls, improving model governance frameworks, or strengthening decision-making procedures, within a defined timeline.

(vi)  In cases of persistent or egregious non-compliance, the IAIC may recommend the temporary or permanent suspension of the non-compliant entity’s AI-related operations, subject to due process and the principles of natural justice.

(vii)Any other regulatory action deemed necessary and proportionate by the IAIC to ensure compliance with the prescribed model standards and to safeguard the responsible development, deployment, and use of high-risk AI systems.

(9)   The IAIC shall establish and publish clear guidelines and criteria for determining the appropriate regulatory actions, ensuring transparency and consistency in its decision-making process.

(10)The IAIC shall encourage the sharing of AI-related knowledge, including datasets, models, and algorithms, through open-source software repositories and platforms, subject to applicable intellectual property rights and the provisions of the Digital Personal Data Protection Act, 2023 and other relevant data protection and governance frameworks as may be prescribed.