• Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • Core Principles of Responsible AI
    • Accountability
    • Fairness
    • Privacy
    • Safety and Security
    • Sustainability
    • Transparency
  • Special Topics
    • AI in Industry
    • Ethical Implications
    • Human-Centered Design
    • Regulatory Landscape
    • Technical Methods
  • Living Dictionary
  • State of AI Ethics
  • AI Ethics Brief
  • 🇫🇷
Montreal AI Ethics Institute

Montreal AI Ethics Institute

Democratizing AI ethics literacy

AI Policy Corner: Singapore’s National AI Strategy 2.0

May 12, 2025

✍️ By Evan Glenn.

Evan is an Undergraduate Student in Political Science and a Research Assistant at the Governance and Responsible AI Lab (GRAIL), Purdue University.


📌 Editor’s Note: This article is part of our AI Policy Corner series, a collaboration between the Montreal AI Ethics Institute (MAIEI) and the Governance and Responsible AI Lab (GRAIL) at Purdue University. The series provides concise insights into critical AI policy developments from the local to international levels, helping our readers stay informed about the evolving landscape of AI governance.


Singapore’s National AI Strategy 2.0

The Singapore National AI Strategy 2.0, released in late 2023, outlines a policy framework intended to “harness AI for the Public Good, for Singapore and the World”.

The plan is divided into three Systems, each containing Enablers with assigned Actions to carry out this goal. 

System One: Activity Drivers

This system relies on Industry, Government, and Research to set the foundation for AI integration and advancement. The Government is the lynchpin of Singapore’s plans, with many of its Actions hinging on public funding and incentives (e.g. for training programs and the development of AI Centers of Excellence). In particular, Singapore is interested in convening AI talent and Industry builders from Singapore and beyond. The Government is also committed to expanding resources and policy guidelines to enhance its Research output.

System Two: People & Communities

This system relies on Talent, Capabilities, and Placemaking to foster the human resources for AI R&D. It reaffirms commitments to introducing training programs and attracting talent. Specifically, Singapore seeks to enable industry and academic exchanges as well as develop an “iconic AI site” to “serve as an intellectual home”. Additionally, Singapore wants to directly encourage industry to explore AI Capabilities, including their own suggestions for AI solutions in its Industry Digital Plans.

System Three: Infrastructure & Environment

This system cites Compute, Data, a Trusted Environment, and a Leader in Thought and Action as the support structure for AI. The Government commits to expanding Compute and Data for use in R&D, while remaining mindful of environmental and privacy risks. For example, the government will create a “data concierge” to control access to public sector datasets. The government also seeks to manage risks through an adaptable, tiered regulatory framework. Finally, Singapore recognizes that AI use has global implications and wants to approach risk management with a mindset of international cooperation.

Developments

Before the release of the NAIS 2.0, Singapore was well on the way to fulfilling some of its outlined actions, such as authorizing the use of the Pair LLM by government officers. Many of the actions were also officially announced in early 2024 at the Committee of Supply Debates. This includes investments for compute resources, scholarships/internships, and an overall investment of “more than $1 billion over the next five years” to support NAIS 2.0. Additionally, guidelines on the use of personal data were published following this event.

More recently, at the February 2025 AI Action Summit in Paris (see The AI Ethics Brief #158 for details), Singapore announced several AI initiatives to address safety risks including a “testbed for best practices around technical testing of GenAI applications” and a report on Singapore’s AI Safety Red Teaming Challenge setting out widely applicable testing methodologies.

Notably, Singapore also announced a collaborative Joint Testing Report with Japan, following through on the collaborative ideals set out in the NAIS 2.0. While the NAIS 2.0 largely relies on general language, Singapore appears to be holding itself to its goals.

Further Reading

  1. The Smart Nation Initiative
  2. The Pair LLM
  3. Singapore’s AI Safety Institute

Want quick summaries of the latest research & reporting in AI ethics delivered to your inbox? Subscribe to the AI Ethics Brief. We publish bi-weekly.

Primary Sidebar

🔍 SEARCH

Spotlight

AI Policy Corner: Texas and New York: Comparing U.S. State-Level AI Laws

What is Sovereign Artificial Intelligence?

AI Policy Corner: The Kenya National AI Strategy

AI Policy Corner: New York City Local Law 144

Canada’s Minister of AI and Digital Innovation is a Historic First. Here’s What We Recommend.

related posts

  • Outsourced & Automated: How AI Companies Have Taken Over Government Decision-Making

    Outsourced & Automated: How AI Companies Have Taken Over Government Decision-Making

  • Evaluating the Social Impact of Generative AI Systems in Systems and Society

    Evaluating the Social Impact of Generative AI Systems in Systems and Society

  • Risks vs. Harms: Unraveling the AI Terminology Confusion

    Risks vs. Harms: Unraveling the AI Terminology Confusion

  • From Case Law to Code: Evaluating AI’s Role in the Justice System

    From Case Law to Code: Evaluating AI’s Role in the Justice System

  • Artificial Intelligence in healthcare: providing ease or ethical dilemmas?

    Artificial Intelligence in healthcare: providing ease or ethical dilemmas?

  • The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices

    The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices

  • Knowledge, Workflow, Oversight: A framework for implementing AI ethics

    Knowledge, Workflow, Oversight: A framework for implementing AI ethics

  • A Matrix for Selecting Responsible AI Frameworks

    A Matrix for Selecting Responsible AI Frameworks

  • The Ethical Considerations of Self-Driving Cars

    The Ethical Considerations of Self-Driving Cars

  • Who Is Governing AI Matters Just as Much as How It's Designed

    Who Is Governing AI Matters Just as Much as How It's Designed

Partners

  •  
    U.S. Artificial Intelligence Safety Institute Consortium (AISIC) at NIST

  • Partnership on AI

  • The LF AI & Data Foundation

  • The AI Alliance

Footer

Categories


• Blog
• Research Summaries
• Columns
• Core Principles of Responsible AI
• Special Topics

Signature Content


• The State Of AI Ethics

• The Living Dictionary

• The AI Ethics Brief

Learn More


• About

• Open Access Policy

• Contributions Policy

• Editorial Stance on AI Tools

• Press

• Donate

• Contact

The AI Ethics Brief (bi-weekly newsletter)

About Us


Founded in 2018, the Montreal AI Ethics Institute (MAIEI) is an international non-profit organization equipping citizens concerned about artificial intelligence and its impact on society to take action.


Archive

  • © MONTREAL AI ETHICS INSTITUTE. All rights reserved 2024.
  • This work is licensed under a Creative Commons Attribution 4.0 International License.
  • Learn more about our open access policy here.
  • Creative Commons License

    Save hours of work and stay on top of Responsible AI research and reporting with our bi-weekly email newsletter.