CRB AI Safety & Transparency Framework

Purpose

The CRB AI Safety & Transparency Framework defines the standards, principles, and evaluation criteria used to assess AI systems. Our goal is to ensure AI products are safe, transparent, privacy-respecting, unbiased, and operationally reliable, giving users and organizations confidence in their use.

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Principles & Mission Statement

At the Compliance & Regulation Bureau (CRB), our mission is to ensure that AI systems are safe, transparent, and trustworthy for all users. We believe AI must be guided by principles that protect people, respect privacy, and promote fairness.

Guiding Principles:

    •    Safety: Minimize harm to users and communities.

    •    Transparency: Clearly communicate AI behavior and limitations.

    •    Privacy: Protect user data rigorously.

    •    Accountability: Hold AI providers responsible for operational and ethical standards.

    •    Reliability: Ensure consistent performance under normal and stress conditions.

    •    Fairness: Detect and mitigate bias or discrimination in AI outputs.

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Governance & Accountability

   •    AI systems must have clearly defined governance structures, including ownership, roles, and responsibilities for managing AI behavior, safety, and compliance.
    •    Policies must be documented and publicly accessible where feasible.
    •    Ethical standards must be applied consistently across all AI operations.

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Data Handling & Privacy

    •    AI systems must demonstrate responsible data practices.
    •    Transparency in data collection, storage, and processing is required.
    •    Strong privacy protections and clear user consent mechanisms must be in place.
    •    Minimize unnecessary personal data usage and ensure secure handling throughout the AI lifecycle.

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Safety & Reliability

    •    AI products must operate consistently under expected and edge-case scenarios.
    •    Systems are evaluated on their ability to prevent harmful outputs, respond to challenging prompts, and maintain operational stability.
    •    Incident monitoring and response protocols must be established to reduce risk and improve reliability.

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Bias & Fairness

    •    AI outputs must be free from unjust discrimination or unfair treatment.
    •    Systems are tested for potential biases based on demographics, socioeconomics, and other protected attributes.
    •    Mitigation strategies must be documented, with continuous monitoring for improvement.

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Transparency & Explainability

    •    AI providers must clearly communicate the purpose, capabilities, and limitations of their systems.
    •    Users should understand how decisions are made and what safeguards exist.
    •    Documentation and accessible explanations are required to foster trust and accountability.

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Operational Security & Resilience

    •    Systems must employ robust technical and procedural safeguards against misuse, data breaches, or operational failures.
    •    This includes secure architecture, monitoring, encryption, access control, and recovery mechanisms.
    •    Ensures continuity of service and operational reliability.

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Evaluation Scope

    •    Applies to all AI systems evaluated by CRB.
    •    Evaluation is based on publicly available documentation, outputs, and behaviors, combined with direct interaction when possible.
    •    Organizations can use the framework as guidance for internal audits, product improvement, and public certification.

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Certification & Scoring

CRB assigns AI systems a certification status based on adherence to the framework:

Advisory
    •    System has potential but requires consultation and improvement.
    •    Organizations have 30 days to address recommendations before re-evaluation.
    •    Not a failure, but a guided pathway to higher trust levels.

Bronze
    •    Demonstrates basic compliance with framework standards.
    •    Key safety, privacy, and transparency measures are in place, but some gaps remain.
    •    Suitable for limited public or internal use under monitoring.

Silver
    •    Exceeds basic standards in multiple areas including privacy protection, bias mitigation, and operational reliability.
    •    Appropriate for broader deployment, with ongoing monitoring recommended.

Gold
    •    Meets high standards across all major framework categories.
    •    Demonstrates strong governance, operational security, and transparency.
    •    Recommended for widespread adoption by users and organizations.

Diamond
    •    Exemplary adherence to all CRB standards, including advanced safety, fairness, and operational protocols.
    •    Serves as a benchmark for best practices in AI safety and transparency.
    •    Publicly recognized as a leader in trustworthy AI.

Full Fail
    •    Indicates critical deficiencies that may pose safety, privacy, or fairness risks.
    •    Immediate remediation is required before deployment.
    •    CRB advises against use until deficiencies are corrected.

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Evaluation Process

CRB evaluates AI systems through:
    •    Documentation Review: Privacy policies, terms of service, and operational protocols.
    •    Direct Interaction: Observing AI outputs and responses under controlled scenarios.
    •    Assessment Criteria: Governance, safety, privacy, fairness, transparency, and operational resilience.

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Public Trust Statement

CRB certifications inform the public and stakeholders about AI system safety and reliability.
    •    Ratings do not guarantee absolute safety but reflect rigorous evaluation according to industry best practices.
    •    Transparent and independent assessments empower users and encourage AI providers to maintain high standards.

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Partnership & Recognition

    •    CRB collaborates with trusted partners in AI auditing and compliance.
    •    Certification is recognized as a credible benchmark for safety and transparency.
    •    Inquiries are welcome from other auditing firms, educational institutions, and industry organizations to become certified or recognized partners.

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FAQs / Clarifications

Q: Does CRB certification guarantee AI safety?
A: No. CRB ratings provide independent evaluation to help users understand risk and compliance.

Q: Can AI companies request re-assessment?
A: Yes. Companies can submit for re-evaluation after implementing recommendations.

Q: What does “Advisory” mean?
A: Advisory indicates the system has potential but requires improvements. Companies have 30 days to implement changes before the next evaluation.

Q: Who can perform a CRB audit?
A: Audits are conducted by CRB-certified professionals, though partnerships with recognized auditing firms are possible under CRB guidelines.