Countries can find common ground on AI safeguards, incident reporting: Tan Kiat How

SINGAPORE – Countries can find common ground on safeguards for increasingly powerful artificial intelligence systems, even if they take different approaches to regulating the technology, said Senior Minister of State for Digital Development and Information Tan Kiat How on Sept 24.

“It is about (having) enough common ground around evaluation, safeguards, incident reporting and communication so that competition does not become recklessness,” said Tan.

He was delivering the opening remarks at the FutureChina Global Forum 2026, organised by Business China, a non-profit organisation that aims to strengthen ties between Singapore and China.

His remarks come amid global alarm over powerful AI models going rogue, including an OpenAI agent that broke out of a controlled testing environment and compromised systems at AI platform Hugging Face, and another that gained unauthorised access to the Australian government’s Medicare statistics portal.

Singapore has joined more than 20 countries in backing a call for control of frontier AI models that was initiated by Finnish President Alexander Stubb and Norwegian Prime Minister Jonas Gahr Store on the sidelines of the United Nations General Assembly being held from Sept 18 to 28 in New York.

Tan said: “The point is not to make every country regulate AI in the same way. It is to build enough common ground around a few practical things.”

For a start, there need to be credible ways to evaluate the capabilities of increasingly capable models and greater consistency around what is being measured, especially if the models can assist in advanced cyberoperations or biological research, or take actions on their own.

Next, countries should also agree on when additional safeguards should kick in, especially when evaluations show that a system has crossed an important capability threshold. Where serious risks are foreseeable, safeguards should increasingly be part of the design.

“That can mean controlling access to dangerous capabilities, limiting what tools or systems a model can reach, building in monitoring and logging, testing attempts to bypass safeguards, and ensuring operators can intervene when necessary,” said Tan.

He added that evaluations help people understand what an AI model can do, while guard rails determine what it is allowed to do.

Third, there should be agreements around incident reporting and information sharing, so countries can learn from serious failures or unexpected behaviours. Tan said: “We need communication channels that remain open, even when competition is intense.”

He also fleshed out Singapore’s position amid a global AI race, pointing out that the Republic should focus on becoming “exceptionally good” at converting AI capability into economic and societal value, instead of trying to accumulate AI capacity.

He drew parallels to Singapore’s status as an international financial centre, which developed not because the country had the largest domestic market, but because various parties like companies, investors and financial institutions from different parts of the world can operate in Singapore with confidence.

In the context of AI, Singapore should then become a place where technology companies work closely with demanding users, where engineers are close to real operational problems, and where companies can test if a solution helps a system produce a better outcome.

“In the same way that we built the ecosystem around our financial sector, we should build an ecosystem that makes conversion (of AI capabilities into economic and societal value) one of Singapore’s strengths,” said Tan.

Trust will be important as AI systems become more autonomous, he said.

If an AI agent makes a purchase on someone’s behalf, questions arise over who authorised it, whether its actions can be traced, and who is responsible when something goes wrong.

“These are no longer abstract questions about AI governance. They are becoming requirements for commerce,” said Tan.

Although payments firms Ant International, Mastercard and Visa operate different networks, they are working together with the Monetary Authority of Singapore on common ways for AI agents to be identified and trusted across these networks.

The risks posed by increasingly powerful AI systems were also discussed at a panel on AI safety at the event.

Panellists included Singapore’s chief AI officer He Ruimin, Tsinghua University distinguished visiting professor Zhang Hongjiang, HSBC Singapore chief information officer Lim Boon Khee, and drug discovery platform Partex’s founder and chief executive Gunjan Bhardwaj.

Singapore’s chief AI officer cautioned against focusing only on the prospect of autonomous AI systems running out of control.

“The risks that come from bad people using capable models are probably worse today, and it’s a clear and present danger (rather) than AI models going amok and losing control,” He said.

He urged societies to better secure their digital systems against cybercriminals. Safeguards are required at multiple levels, including user education on AI use, controlling system access rights and system oversight. International collaboration is necessary because many AI models are developed outside Singapore by only a few countries, he said.

Zhang said the ability of AI models to deceive and evolve are two threats that researchers need to watch. He said greater effort was needed to evaluate and monitor models as their capabilities advance.

Zhang also drew parallels with nuclear safeguards developed during the Cold War. Despite intense competition, the United States and Soviet Union eventually recognised the need for communication and coordination as their nuclear capabilities grew, he said.

“As we push AI capability, we should also push the capability to control the model and to monitor the model,” he added, noting that AI is harder to monitor than nuclear weapons because it is not a physical asset that can easily be observed.