Catherine Nakalembe

We can predict droughts, floods, weeks, even months in advance, yet we still see the same crises unfold.

crop failure, economic and environmental devastation, and displacement, the same crises that have trapped farming communities for generations.

This is obviously not a prediction problem, it's a translation problem, one that I came to realize painfully in 2015.

Equipped with the best tools available at the time, including that very expensive fancy drone, I spent August 2015 with my team in Karamoja documenting yet another failed cropping season, one that I predicted months earlier using satellite data.

This was part of the worst drought in East Africa in decades, affecting 30 million people in Uganda, Kenya, Somalia and Ethiopia.

After my fieldwork, I did something researchers rarely do.

I went straight to the office of the prime minister, and 24 hours after my second presentation to several ministers, food trucks were dispatched to Karamoja on September 26, 2015, exactly 10 years this week, which marked the first time the office used satellite data to trigger an emergency response.

Following this, I helped design a program that would proactively release financing to support alternative employment for communities affected by drought.

This program went on to support 450,000 people over five years, saving the government millions in emergency response and deploying several projects that included environmental restoration.

But what haunted me then, and is still true today, is this.

If we could mobilize emergency response within 24 hours, why couldn't we prevent this predictable crisis from unfolding?

This paradox has deepened because today's capabilities make 2015's best look primitive.

We have over 8,000 satellites and AI models and computational power that will make predictions using this data with other data sets to produce information at unprecedented scales and at unprecedented speeds.

If you can combine this with advances in crop science, mobile banking, mechanization, the possibilities seem limitless.

Yet, just last year in 2024, nearly one in three people were worried about where their next meal would come from.

Climate disasters have more than doubled since the 1980s.

So the question is, why does this keep happening?

I would like to tell you a story that will help you bridge the gap between why we have such incredible capabilities and are unable to deliver clear information for a farmer, for example, to increase their yield, save their produce by reducing post-harvest losses, and having alternative income so they can survive through tough times.

We have incredible technology

but we're missing translators to connect our predictions of that drought, for example, to real, tangible solutions that can get a farmer what they actually need to thrive.