Singapore Consensus to advance AI that is trustworthy, reliable and secure

A conference convened to discuss the importance of AI safety research and the need for an international consensus has resulted the publication of The Singapore Consensus on Global AI Safety Research Priorities” (The Singapore Consensus).

The Singapore Consensus, developed at Singapore Conference on AI: International Scientific Exchange on AI Safety” (SCAI: ISE), has identified three broad areas of AI safety research priorities:

Risk assessment

The primary goal of risk assessment is to understand the severity and likelihood of a potential harm, which can then help prioritise risks and determine whether action needs to be taken. The research areas in this category involve developing methods to measure the impact of AI systems for both current and future AI, enhancing metrology to ensure that these measurements are precise and repeatable, and building enablers for third- party audits to support independent validation of these risk assessments.

Development

AI systems that are trustworthy, reliable and secure by design give people the confidence to embrace and adopt AI innovation. Following a classic safety engineering framework, the research areas in this category involves specifying the desired behaviour, designing a system that meets the specification, and verifying that the AI system meet its specification.

Control

In engineering, “control” usually refers to the process of managing a system’s behaviour to achieve a desired outcome, even when faced with disturbances or uncertainties, and often in a feedback loop.

The research areas in this category involve developing monitoring and intervention mechanisms for AI systems, extending monitoring mechanisms to the broader AI ecosystem to which the AI system belongs, and societal resilience research to strengthen societal infrastructure (e.g. economic, security) against AI-enabled disruption and misuse.

In her opening remarks at SCAI: ISE, Singapore Minister for Digital Development and Information, Mrs Josephine Teo, shared that it is important to build stronger pathways between the research world and policy making world to translate AI safety research into real effective policies to govern AI well. Through this scientific exchange, The Singapore Consensus aims to bridge discussions between AI scientists and AI policy makers, as part of a continuous dialogue to help governments strike the delicate balance of safety and innovation based on scientific evidence.

To influence policy-making, the The Singapore Consensus will be presented to digital ministers attending the ministerial roundtable at the Asia Tech x Singapore Summit (ATxSummit) from 28-29 May 2025. The end-goal is to create a virtuous cycle of trust and, more importantly, ensure that AI is harnessed for the public good.

Singapore remains committed to a scientifically driven and evidence-based approach to AI governance. The AI Verify Foundation (AIVF) launched the AI Verify Testing Toolkit in 2023 and Project Moonshot in 2024 to test traditional and generative AI models respectively. Singapore’s IMDA along with AIVF also released the Model AI Governance Framework for Gen AI in 2024 that provided a systematic and balanced approach to address Gen AI concerns while facilitating innovation. 

IMDA, in partnership with Humane Intelligence, also conducted the world’s first multicultural and multilingual red-teaming exercise in 2024, publishing the Singapore AI Safety Red-Teaming Challenge Evaluation Report on it thereafter. AIVF further launched the Global AI Assurance Pilot earlier this year to help codify emerging norms and best practices around technical testing of generative AI applications.