Singapore and Rwanda have introduced the world’s first AI Playbook for Small States to shape inclusive global discourse on harnessing the potential of AI. First announced at the Asia Tech x Singapore Summit 2024 on 30 May 2024, the AI Playbook is developed by Singapore’s Infocomm Media Development Authority (IMDA) in collaboration with Rwanda’s Ministry of Information Communication Technology (ICT) and Innovation, with consultations taking place with Digital Forum of Small States (“Digital FOSS”) members since the start of the year.
The Playbook addresses common challenges small states face in adopting and harnessing the potential of AI, such as availability of resources and funding, access to data and AI talent, fostering a trusted environment such as developing holistic frameworks and practical testing tools such as AI Verify.
Given the rapidly evolving nature of AI, the Playbook is shaped as a living document that continuously pulls together the collective experiences and strategies from small states.
More information and the AI Playbook itself can be found in the following links.
Understanding and implementing responsible AI is a continuous journey, and every organisation is at a different stage. Whether you’re just beginning to explore AI governance or you’re looking to refine an established framework, our resources are designed to guide you through every step of this important process.
Singapore’s collection of guidance documents and tools offers practical insights and actionable practices tailored to your organisation’s level of maturity in AI governance. From foundational frameworks for those starting out, to advanced practices and technical tests for more sophisticated AI implementations, our materials provide the support you need to develop and enhance your AI governance capabilities.
Use our flowchart to assess where your organisation currently stands in its responsible AI journey. This will help you identify the right resources and tools to move forward confidently and responsibly.
Looking to test your AI models? Explore how AI Verify and Project Moonshot can help you assess and enhance your AI systems.
Find out which evaluation tools are best suited to your needs and how they can help you align with key AI governance principles and build trust with your stakeholders.
Learn to create custom plugins to enhance AI Verify’s capabilities.
In this video, we will walk you through the entire process, from architecture to customising your first plugin. This video is tailored for developers of all levels who want to enhance and contribute to the open-source community. Here’s what we will cover:
By the end of this video, you will have the skills to customise plugins to fit your unique requirements and the knowledge to contribute effectively to AI Verify.
“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.”
– Wael William Diab, Chair, ISO/IEC JTC1 / SC42 on AI standards
The AI Verify Foundation welcomes initial comments and feedback on this draft release, which can be sent to [email protected]. We are currently establishing a more convenient method to receive and incorporate feedback from the community, and will update in due course.
Your organisation’s background – Could you briefly share your organisation’s background (e.g. sector, goods/services offered, customers), AI solution(s) that has/have been developed/used/deployed in your organisation, and what it is used for (e.g. product recommendation, improving operation efficiency)?
Your AI Verify use case – Could you share the AI model and use case that was tested with AI Verify? Which version of AI Verify did you use?
Your experience with AI Verify – Could you share your journey in using AI Verify? For example, preparation work for the testing, any challenges faced, and how were they overcome? How did you find the testing process? Did it take long to complete the testing?
Your key learnings and insights – Could you share key learnings and insights from the testing process? For example, 2 to 3 key learnings from the testing process? Any actions you have taken after using AI Verify?