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The Alliance Charter

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Schedule 1

Updation Date and Time

10 May 2025

Schedule 1 – AI Standards Classification and Implementation

 

Part A: Imperatives associated with AI Standards and Principles

 

        (1)         Pre-Regulatory Imperatives: Pre-regulatory imperatives encompass standards/principles that anticipate future regulatory needs and help shape emerging governance frameworks. These imperatives categorize approaches that guide innovation while ensuring AI systems remain ethical, scalable, and sustainable as new regulations develop. Standards classified under pre-regulatory imperatives reflect proactive governance, establishing frameworks adaptable to evolving regulatory landscapes.

 

        (2)         Regulatory Imperatives: Regulatory imperatives classify standards/principles designed to align with existing legal and regulatory requirements. These imperatives characterize frameworks that help organisations comply with current laws and regulations, ensuring AI systems meet necessary legal, ethical, and operational benchmarks. Standards attributable to regulatory imperatives are particularly significant for industries operating in highly regulated environments.

 

       (3)         Post-Regulatory Imperatives: Post-regulatory imperatives are attributable to standards/principles developed to enhance and refine existing regulatory frameworks. They categorize guidelines for implementation and compliance after regulations have been established, ensuring AI systems operate within legal boundaries while optimizing performance. Standards within this imperative address gaps in regulatory frameworks and focus on operational excellence within established legal parameters.

 

       (4)         Miscellaneous Imperatives: Miscellaneous imperatives characterise standards/principles that apply universally across all stages of governance (pre-regulatory, regulatory, post-regulatory). They encompass foundational frameworks adaptable across different industries, regions, or use cases, addressing cross-cutting concerns such as interoperability, ethical considerations, and stakeholder inclusion. Standards classified under miscellaneous imperatives ensure consistency in AI governance regardless of regulatory stage.

 

Part B: Imperative Matrix for AI Standards and Principles

 

AI Standards and Principles must address any of the four key imperatives—technical, commercial, legal, and ethical—at various stages of governance (pre-regulatory, regulatory, post-regulatory). The following table outlines how each imperative applies to different types of standards and principles:


Imperative

Post-Regulatory

Regulatory

Pre-Regulatory

Miscellaneous

Technical

  • System interoperability enhancement

  • Quality assurance protocols

  • Operational framework alignment

  • Compatibility requirements

  • Performance standards

  • Future technology innovation

  • Scalability protocols

  • Adaptability mechanisms

  • Universal benchmarks

  • Cross-domain protocols

  • Common technical frameworks

  • Integration guidelines for legacy systems

  • Predictive analytics for future tech trends

  • Prototyping frameworks for emerging technologies

  • Open-source collaboration standards

  • Best practices for technical documentation

Commercial

  • Market acceptance facilitation

  • Operational viability metrics

  • Implementation efficiency metrics

  • Value proposition development

  • Compliance support systems

  • Business operation guidelines tailored to sectors

  • Industry-specific protocols for AI applications

  • Market preparation guidelines

  • Trend anticipation methodologies

  • Cross-market applicability frameworks

  • Universal business practices

Legal

  • Compliance verification processes

  • Dispute minimisation strategies through arbitration clauses

  • Audit frameworks for accountability

  • Regulatory adherence frameworks with checklists

  • Legal requirement mapping for various jurisdictions

  • Enforcement mechanisms for compliance violations

  • Proactive compliance frameworks anticipating regulatory shifts

  • Future regulation anticipation strategies based on global trends

  • Cross-jurisdictional frameworks

  • Universal legal principles promoting fairness and justice

Ethical

  • Rights protection mechanisms ensuring user privacy and data security

  • Privacy standards aligned with global best practices

  • Accountability frameworks for AI decisions

  • Transparency protocols mandating disclosure of AI decision-making processes

  • Trust-building mechanisms through stakeholder engagement

  • Proactive ethical frameworks encouraging responsible innovation

  • Responsibility protocols defining ethical obligations of AI developers

  • Core ethical principles guiding AI deployment across sectors

  • Fundamental rights protection ensuring inclusivity and fairness


Part C: Stakeholder-centricity

 

   (1)         For every principle or standard, it is required to specify which specific facet of a standard or a principle is attributable to which stakeholder, as per the table below:



Government

Community

Organisations

Central Government Ministries / Departments

Academic Institutions / Researchers

Large Enterprises

Regulatory Bodies

Open-Source Communities

Micro, Small & Medium Enterprises

Policymakers

Technical Standards Bodies

Start-ups

Public Sector Organisations

Ethics Committees

Technology Providers

Parliament/Legislative Bodies

Civil Society Organisations

Intergovernmental Organisations

National Security Agencies

Industry Consortiums

Financial Institutions

State/Regional Government Ministries / Departments

Professional Associations

Healthcare Providers

Sectoral Regulators

Data Science Collectives

Educational Institutions

Local Administrative Bodies

Digital Rights Groups

Media Organisations

Advisory Councils

Consumer Advocacy Groups

Industry Associations

Inter-ministerial Committees

Scientific Research Institutes

Sector-specific Technology Firms

Policy Implementation Agencies

Traditional / Indigenous Knowledge Groups

Development Partners

AI Safety Institutes

Regional Technical Communities

Telecommunications Providers

Judicial Institutions

Legal Experts

Digital Service Providers

Constitutional Bodies

Capacity Building Networks

Non-Profit Organisations



   (2)         ISAIL.IN's principles are non-binding and for consultative purposes only. They are distinct from Article 28 of the Charter.


Part D: Cross-Cutting Considerations

 

(1)   AI standards and principles may address multiple imperatives simultaneously, ensuring a holistic approach to standardisation.

(2)   The classification of standards may evolve based on:

(a)    Technological advancements,

(b)   Market conditions,

(c)   Regulatory developments,

(d)   Ethical considerations.

(3)   Flexibility in implementation of AI standards is essential to allow for:

(a)    Modular design,

(b)   Scalable frameworks,

(c)   Adaptable mechanisms,

(d)   Context-sensitive approaches.

(4)   Regular reviews with respect to AI Standards shall be conducted to assess:

(a)    Effectiveness of the standard

(b)   Stakeholder feedback,

(c)   Emerging challenges

(d)   Necessary updates or revisions.

 

Part E: Standard Development Essentials

 

(1)   Each standard must be evaluated against:

(a)    Governance stage appropriateness (pre-regulatory, regulatory, post-regulatory),

(b)   Alignment with technical, commercial, legal, and ethical imperatives,

(c)   Feasibility of implementation,

(d)   Stakeholder impact.

 

(2)   The development process should include:

(a)    Clear scope definitions

(b)   Stakeholder consultation at relevant stages,

(c)   Technical validation through expert review,

(d)   Policy alignment with existing or emerging regulations.

 

(3)   Documentation shall specify:

(a)    The primary governance stage (pre-regulatory, regulatory, post-regulatory),

(b)   Key imperatives addressed (technical, commercial, legal, ethical),

(c)   Implementation requirements,

(d)   Review mechanisms for periodic updates.

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