As organisations deploy systems with Artificial Intelligence (AI), it is important to be transparent about your AI systems to build trust with our stakeholders.
ISO/IEC 42001:2023 is a first of its kind international standards designed to ensure broad responsible adoption of AI. The novel approach, in conjunction with the family of standards that ISO/IEC JTC 1/SC 42 is developing, provides a portfolio of international standards that countries and regions can rely on to enable trustworthy and transparent AI.
This mapping between AI Verify Framework and ISO/IEC 42001 demonstrates Singapore’s strong support in advancing global harmonisation in a practical way. It also shows the growing number of countries that are leveraging ISO/IEC 42001 to enable trustworthy AI adoption.
The framework has 4 key elements: Principles, Outcomes, Processes, Evidence
Where possible (e.g., not compromising IP, safety, or system integrity), identify appropriate mechanisms in the AI lifecycle to inform end users, subjects and other relevant parties about necessary information regarding the AI system (e.g., the purpose, criteria, limitations, impact, and risks of the decision(s) generated by the AI system) in an accessible manner
Design an in-house policy on communication to consumers that articulates the principles for transparency
e.g., define the purpose and context of communication to determine how and what to communicate. Use visualisations or other methods to ease non-technical stakeholders understanding of AI system functionality
Internal documentation (e.g., policy document)
Documentary evidence of an in-house policy on communication to consumers that articulates the principles for transparency, e.g., define the purpose and context of communication to determine how and what to communicate
The framework has 4 key elements: Principles, Outcomes, Processes, Evidence
Where possible (e.g., not compromising IP, safety, or system integrity), identify appropriate mechanisms in the AI lifecycle to inform end users, subjects and other relevant parties about necessary information regarding the AI system (e.g., the purpose, criteria, limitations, impact, and risks of the decision(s) generated by the AI system) in an accessible manner
Design an in-house policy on communication to consumers that articulates the principles for transparency
e.g., define the purpose and context of communication to determine how and what to communicate. Use visualisations or other methods to ease non-technical stakeholders understanding of AI system functionality
Internal documentation (e.g., policy document)
Documentary evidence of an in-house policy on communication to consumers that articulates the principles for transparency, e.g., define the purpose and context of communication to determine how and what to communicate
The framework has 4 key elements: Principles, Outcomes, Processes, Evidence
For every principle, there are desired outcomes. It could be technical and non- technical processes alongside with technical tests where applicable
Testing processes are actionable steps to be carried out to achieve the desired outcomes
These processes are validated by documentary evidence
Crosswalks 
Process Checks 
The testing framework (Generative AI) is available in a software tool. It can help you:
The AI Verify Testing Framework is also complemented by technical testing tools for Traditional AI and Generative AI.
Demonstrate and document responsible AI practices
Ensure responsible AI practices are in place
Independently validate your client’s responsible AI implementations
Reference to inform best practices and standards development in AI testing
AI Verify was developed in consultation with companies from different sectors and of different scale. These companies include – AWS, Basis.AI, DBS Bank, Google, Meta, Microsoft, Singapore Airlines, NCS (part of Singtel Group), Land Transport Authority, Standard Chartered Bank, UCARE.AI, and X0PA.AI.
AI Verify Testing Framework for traditional AI and software Toolkit was launched as a Minimum Viable Product (MVP) for international pilot and feedback by IMDA and PDPC.
AI Verify Testing Framework and Toolkit was open-sourced in GitHub.
The updated AI Verify Testing Framework was released. The testing framework has been enhanced to address risks posed by Generative AI. With this update, companies can now apply AI Verify Testing Framework for both traditional and Gen AI use cases.
