AI Transparency and Explainability Checklist

This checklist assesses the organization's AI transparency practices, explainability mechanisms, and documentation standards based on ISO 42001, CIS Controls, and NIST CSF frameworks.

Assessment Information

Organization Name:		Assessment Date:
Assessor Name:		Assessment Type:	Pre-Engagement / Post-Engagement

Compliance Status Legend

Status	Description
Compliant	The organization fully meets the requirements of the control.
Partially Compliant	The organization partially meets the requirements of the control.
Non-Compliant	The organization does not meet the requirements of the control.
Not Applicable	The control is not applicable to the organization's environment.

AI Transparency and Explainability Controls

6.1 AI Transparency Policy

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.1	The organization has established a formal AI transparency policy that defines requirements for disclosing AI use, capabilities, limitations, and decision-making processes to stakeholders.			Develop and implement a formal AI transparency policy that defines requirements for disclosing AI use, capabilities, limitations, and decision-making processes to stakeholders. Ensure the policy is approved by leadership and communicated to all relevant personnel.

6.2 AI Explainability Mechanisms

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.2	The organization has implemented appropriate explainability mechanisms for AI systems based on risk level, use case, and stakeholder needs.			Implement appropriate explainability mechanisms for AI systems based on risk level, use case, and stakeholder needs. Develop guidelines for selecting and implementing explainability techniques for different types of AI systems.

6.3 AI Decision Documentation

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.3	The organization has established processes to document and retain records of AI system decisions, especially for high-risk or high-impact use cases.			Establish processes to document and retain records of AI system decisions, especially for high-risk or high-impact use cases. Implement logging mechanisms that capture decision factors, confidence levels, and other relevant metadata.

6.4 AI System Documentation Standards

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.4	The organization has developed and implemented comprehensive documentation standards for AI systems, including intended use, limitations, performance metrics, and known issues.			Develop and implement comprehensive documentation standards for AI systems, including intended use, limitations, performance metrics, and known issues. Create templates and guidelines for consistent documentation across all AI systems.

6.5 Stakeholder Communication

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.5	The organization has established processes for clear communication with stakeholders about AI system capabilities, limitations, and potential impacts.			Establish processes for clear communication with stakeholders about AI system capabilities, limitations, and potential impacts. Develop communication templates and guidelines for different stakeholder groups and use cases.

6.6 Human Oversight Mechanisms

Control ID	Control Description	Compliance Status	Evidence	Remediation
TRANS-6.6	The organization has implemented appropriate human oversight mechanisms for AI systems based on risk level and use case, including review processes and override capabilities.			Implement appropriate human oversight mechanisms for AI systems based on risk level and use case, including review processes and override capabilities. Define roles and responsibilities for human oversight and establish escalation procedures.

Assessment Summary

Total Controls	Compliant	Partially Compliant	Non-Compliant	Not Applicable	Compliance Score
6	0	0	0	0	0%

Recommendations

Approval

Assessor Signature:		Date:
Client Signature:		Date: