Catherine Nakalembe

Fast forward, I had the opportunity to not only do fieldwork back home.

It got me to be able to learn how things actually work because I spent a lot of time in the field.

Data is the new oil.

There's a lot of investment in data infrastructure, a lot of investment in methods, a lot of publications.

It seems really exciting.

It seems like we're breaking a lot of boundaries, a lot of barriers.

But in reality, if you were to visit my sister, who has a farm and is trying to grow maize,

None of what I do has anything to do with what she has to do.

I could do my very best analysis for her, but it's disconnected from the resources that she has access to.

So it does not tell her where the fertilizer is, where the seeds are, when to really plant in reality.

So that's one part of it.

Sometimes we think about what satellite data and AI, et cetera, can do in agriculture.

I think a lot of people think about it the same way as how chat GPT enables you to write an email.

You can immediately check that the text is wrong.

You can correct it, right?

But it's gotten information from a lot of text that's been digitized.

Agriculture has not been digitized.

There's not a lot of text from which my model will learn from to give me the right sentence.

So in the context for my sister, who has some coffee here, some maize here, I think there was cacao too.

Her field is not represented in existing data.