AI Is Not an Efficiency Tool for Humanitarian Causes with Nur Hafiza Mutalif

Fresh out of the studio at the Dataiku Summit Singapore 2026, Nur Hafiza Mutalif, Assistant Head of International Affairs at the Singapore Red Cross, joins us to explore why the humanitarian sector distrusts AI, and what her team built once they worked through that scepticism. Coming to this from international law rather than data science, Nur Hafiza explains why the sector's caution is a feature rather than a lag: humanitarian work rests on doing no harm and on neutrality, and any solution must clear that bar before it clears a business case. Dataiku cleared that bar. Its pro bono experts taught the team how the models worked and let them set the boundaries — which is what earned their confidence. Hafiza walks through the disaster surveillance pipeline that freed four people from daily collation, and the Thailand leptospirosis model forecasting outbreaks from case and climate data. She argues AI should never be justified on efficiency, that data efficiency itself carries risk, and that acting on a forecast demands low-regret choices. Closing the conversation, she shares why capability outlasts any model.

"We cannot see efficiency, too, I think what I should see, as a humanitarian organization, is datasets and the different cases around the world be compressed into something that simplifies value and help us better serve communities." - Nur Hafiza Mutalif

Profile, Nur Hafiza Mutalif, Assistant Head of International Affairs, Singapore Red Cross

LinkedIn: https://www.linkedin.com/in/nurhafizaab/

Episode Highlights:
[00:00] Quote of the Day by Nur Hafiza Mutalif from Singapore Red Cross
[00:55] Three angles: distrust, what they built, where the line sits
[01:45] From international law to leading an AI project
[02:53] What made a cautious team comfortable with AI
[03:24] Pro bono experts who did not impose solutions
[04:04] Attention is a luxury for humanitarian organisations
[05:13] "We curate, we don't create" — countering compassion fatigue
[05:59] Do no harm, neutrality, and innovating with care
[07:06] Why AI must not be treated as an efficiency tool
[07:55] Disaster surveillance: four people, days reclaimed quarterly
[09:09] Does AI only automate the boring work?
[10:24] The Thailand leptospirosis outbreak prediction model
[11:21] Getting humanitarians comfortable acting on a prediction
[12:47] Where AI changes the disaster cycle most
[13:44] What outsiders get wrong about data efficiency
[14:38] The line AI must not cross at the Red Cross
[15:40] Why internal capability beats the models themselves
[16:33] Where an organisation with no data team starts
[17:19] The question people ask, and the one they should
[18:04] AI as a cross-cutting theme over five years
[19:01] Closing

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.