I'm Daniel Toh, a communications professional in Singapore. I've handled media relations for the Ministry of Defence, represented residents at Meet-the-People Sessions, and I'm now studying how AI should be governed as organisations adopt it.
My work has moved between communications, policy and AI governance. Each field asks a different question about the same thing: whether people can trust the institutions that serve them.
How do we explain it?
Media relations at MINDEF, documentary scripting at CNA Insight, and newsroom writing before that.
What should we do about it?
Policy research on social cohesion and mobility, and casework that shows how policy lands on real households.
Does the technology deserve our trust?
Governance frameworks, risk management and red-teaming, studied at SMU and applied to how organisations deploy AI.
I take something complex, whether a policy, a defence technology or an AI model, and make it relevant to the people it affects.
From a recruitment hotline to AI governance – open any chapter for the details.
Republic of Singapore Navy, Navy Recruitment Centre
National Service put me on the front line of public engagement: recruitment fairs, a public hotline, and matching applicants to the vocations that suited them. I finished with an Outstanding performance evaluation.
Nanyang Technological University, SGCarMart, CNA Insight
I read English at NTU and graduated with First Class Honours. Along the way I wrote daily automotive news, scripted a weekly current-affairs documentary series for CNA, and spent a semester at Kyushu University's School of Design.
Ministry of Defence, Assistant Manager, Media Relations
At MINDEF's Communications Organisation I worked on how the public sees National Service and national defence, and looked after the defence technology portfolio, which meant explaining some of Singapore's most technical work to general audiences.
Coverage I secured across local, regional and international press.
Kampong Glam Meet-the-People Session, Resident Casework Volunteer
I've handled more than 100 resident cases alongside the Member of Parliament and grassroots leaders. There, I've interacted with residents in need, learned how policy actually reaches a household, and represented their needs to relevant public agencies.
I explain the schemes that apply, draft tailored recommendations to the agencies involved, and coordinate across them so residents get whole-of-government support rather than a string of separate replies.
Singapore Management University, YP Policy Unit
I'm now completing an Industry Graduate Diploma in Generative AI, Large Language Models and AI Governance at SMU, and contributing research to the YP Policy Unit on social cohesion and social mobility.
My SMU coursework treats governance as a process that runs through an AI system's whole life, not a checklist at launch. Select a stage to see what an AI governance framework looks like.
Deciding whether AI is the right tool at all, and defining the problem, stakeholders and acceptable risk before anything is built.
Choosing data and models with governance in mind: provenance, documentation and the controls the system will need later.
Testing that the system does what it should, including model evaluation and red-teaming to find failures before users do.
Releasing with guardrails, clear accountability, and communication to the people the system will affect.
Watching real-world behaviour for drift, misuse and harm, with a clear way to escalate when something goes wrong.
Revisiting whether the system is still fit for purpose as data, laws and public expectations change.
Decommissioning responsibly: handling data, users and dependencies when a system is withdrawn.
Recent writing and updates.
I'm open to conversations about roles in communications, public policy and AI governance, and always happy to compare notes with people working on the same questions.