Catherine Nakalembe

I wouldn't be able to see that.

Yeah.

This is a really good question.

For me, what I think is, it's more about the why we're doing it.

What is valued in academia versus...

what will be valued on the ground, sometimes completely different things, right?

It's okay to develop models, to publish papers, to create platforms, to measure everything the best possible way.

That is okay.

It is not okay to say that we are very good at measuring this and this is how it's going to help 10 million farmers.

somewhere on the continent of Africa or Asia.

Very different.

Because it's like any model that you can imagine.

It is so far, far away from...

the reality of an everyday person.

All this obsession with, you know, oh my God, I wrote this, or this model works better than this, and everybody's LinkedIn posts are getting more polished and longer, et cetera, like that kind of thing.

But when you go to this scenario I was describing in Madagascar, there was not a single person who worked at a farm who had a smartphone.

And so they do not know ChatGPT.

ChatGPT has not done anything in their life

And what that means is that all of these things literally do not change anything for them.

So if I'm like, we are going to figure out how to make this farmer find what we're doing relevant.