Model Regulation Framework

Governing Digital Innovation with Accountability

Regulations are essential to ensure that digital systems work for the public good — without stifling innovation. The WDG Model Regulation Framework provides ready-to-adapt regulatory text and guidance to help governments, agencies, and industry bodies bridge the gap between ethics and enforcement.

What Is This Framework?

This model regulation offers a template law and set of rules to guide how digital systems, especially those involving AI and personal data, are developed, deployed, and monitored.

It helps ensure:

Rights Protection

Rights are protected through comprehensive safeguards and enforcement mechanisms

Risk Anticipation

Risks are anticipated through proactive assessment and mitigation strategies

Innovation Within Bounds

Innovation remains possible within clear regulatory boundaries and guidelines

Balancing Innovation and Protection

The framework is designed to strike a constructive balance:

Innovation Enabler

  • Sandbox programs for AI trials
  • Open data access for R&D
  • Model deployment flexibility
  • Rapid iteration allowed

Protection Measure

  • Risk-based approval processes
  • Consent and data minimization rules
  • Algorithmic audit requirements
  • Mandatory human oversight on high-risk use cases

Rather than over-regulating early, the model proposes tiered risk categories with graduated responsibilities.

Sample Regulatory Sections Include:

Definitions & Scope

What is covered, who is bound

  • Clear definitions of AI systems and digital platforms
  • Jurisdictional scope and applicability criteria
  • Exemptions and special considerations for specific sectors

Digital Rights Enforcement

Access, redress, appeal

  • Individual rights to access, correct, and delete personal data
  • Appeal mechanisms for automated decision-making
  • Redress procedures for algorithmic harm or discrimination

AI Risk Classification & Obligations

Tiered approach to AI system regulation

  • Risk-based classification system for AI applications
  • Graduated obligations based on risk levels
  • Specific requirements for high-risk AI systems

Data Handling Standards

Storage, sharing, deletion

  • Data minimization and purpose limitation principles
  • Secure storage and transmission requirements
  • Data retention and deletion policies

Transparency Requirements

Documentation, explainability

  • Algorithmic transparency and explainability standards
  • Public reporting requirements for AI system performance
  • Documentation standards for system development and deployment

Regulatory Bodies & Oversight

Governance and enforcement mechanisms

  • Establishment of regulatory authorities and their powers
  • Oversight mechanisms and compliance monitoring
  • Inter-agency coordination and international cooperation

Penalties & Remedies

Non-compliance consequences

  • Graduated penalty structure based on violation severity
  • Remedial actions and corrective measures
  • Appeal processes for regulatory decisions

Each section includes sample language, policy rationale, and global precedents.

Implementation Guidance

Included with the framework are:

Adoption Timeline & Checklist

Step-by-step guidance for national or regional implementation

Global Standards Alignment

Examples of alignment with EU AI Act, OECD AI Principles, and other frameworks

Regulatory Sandbox Templates

Ready-to-use templates for pilot programs and controlled testing environments

Living Framework Updates

Continuous evolution with community input and emerging technology considerations

This is a living framework — evolving with community input and new tech realities.

Apply the Framework

Use This Framework

Access the full regulation text and modular components

Request Adaptation Help

Form to request assistance adapting for your jurisdiction or institution

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Optional CTA for legal/policy experts to provide improvements