AI governance
Scarcity has shifted, not disappeared: The premise of AI abundance needs sharper evidence
Singapore needs tractable policy questions about AI, not grand narratives about a post-scarcity future
If AI is a public good, nationalisation should be considered
A technology so consequential, potentially disruptive and paradigm-shifting cannot be managed through basic regulation alone
The parrot argument about AI is dead. The question now is permission
Adopting AI does not guarantee safety. But not adopting it guarantees exposure
Will the step forward in frontier AI mean a step backward in cybersecurity?
Organisation leaders must rethink their approach to managing IT risks
AI’s future at work looks more like OpenClaw than OpenAI
An eagerness to move faster will result in companies allocating excessive manpower to maintain systems
Cybersecurity’s Tower of Babel: Why we are still lost in translation
When leadership teams and security functions operate in different languages of risk, critical signals might be dismissed until the problem has escalated
The coming AI-driven ‘abundance’ shock
Singapore has long excelled at navigating scarcity, but the emerging challenge is structurally different
Singapore faces AI’s challenge early, and it’s about the data you can prove
Governance that lives only in policy documents fails in production; it must be embedded in how data is collected, shared and used
AI governance: The summit stage is necessary but it isn’t sufficient
As the geostrategic environment deteriorates, we must accelerate efforts to boost international coordination and build governance infrastructure
When principle meets power: the Anthropic-Pentagon stand-off
What is the future of AI governance – especially in military and national security contexts?
