Smart Talks with IBM and Malcolm Gladwell: Reshaping the Future with Women in AI

Chimka Monk Buyer, co founder of Agrily. Chimka was recently named one of IBM's Women Leaders in AI for her work with Agrily, a digital platform that helps farmers make smart decisions about their crops using IBM technology. Right now, women make up an estimated of the AI workforce globally. In their work, both Carla and Chimpka breakdown barriers in the field and help make it more inclusive. Let's dive in. Well, Welcome, It's a pleasure to meet you all, the two of you.

Carla your new to IBM. I'm told tell me where you came from and what brought you to I be am. I'm a twenty one you're veteran of the tech industry that put myself through architecture school, running restaurants and bars. And I say that because that's really informed who I am and how I operate in the world. I came to IBM for a very specific reason for starters. What an iconic brand. It's not just any tech company, it's

the foundation of a whole industry. But secondly, the vale use of the company really resonated with me, and the heritage in the company as it stands with respect to diversity inclusion was in particular very appealing to me. So that's a big reason why I'm here. Yeah, Jim, what brought you into this world of AI and associated things?

How I started it? I was a full right master's student from two thowy and then in the final year of my master's I teamed up with a bunch of international students from Taiwan, India and Brazil, and then we

came up this idea. Because I was doing the research and the rule of development and ongoing, I found that interesting traditional business that is more about farming, and then we just decided to work to build their mobile app that could be connected to AI later it's a long term plun and then just fight against climate change most importantly and then also solved like other challenges based by small holders. Tell me exactly how this works. So I'm a farmer in Mongolia and I have a I have

a smartphone and I I download the ugly app. What does it help me do? So, if you're a farmer malcom Mongolia, it's three to download. You will download the app and then depending on the country, you have a like farmer and code because you don't really just like start farming on your own, because you just get a permission to use a certain land right and then you're using the water resource, et cetera. So you have a farmer's code, and then you start putting your farmer's code.

And then because every month, you know, you have to report like how much yield you're getting, you're just like answering some questions and then like at the end of quarter your report will be ready to download for agronomous Yeah, yeah, So how does tell me? Carla chime in on this. I'm just curious about. So how does IBM act as

a partner here? What is IBM doing to help make this app um real So um So Chimp is actually leveraging many of our Watson products, including our weather channel product um for agrily, and I'll let her talk about how she's leveraging them to put them together. There is an existing set of tools which IBM has available which people like China can come and customize for their own purposes.

That's right, like depending on like geography, for example, in the Eastern like if you're Eastern part Eastern province, or if you're um like central province of one going the weather is very different. You know, you have to know about your short term weather, what is your long term weather? Uh So our app provides you daily, weekly, monthly, and

even annual weather forecasts book it's very location specific. And then also like if you have um let's say, if you're in the Central problem one of the Central provinces and you want to contact or interact with other farmers, there's a forum discussion session that you can just register and then start interacting with other farmers from your area.

Uh And then also there's a marketplace like you know, that's the most difficult part that we're trying to implement because there's no market market ecosystem and mongolia for example, Uh, that you want to sell you want to sell your produce like in the local area or in the to the urban area, so that you can use the app, because maybe some restaurants from the open market they can contact you through the through the app saying that we want I don't know, like tones of like potatoes or carrots.

And then just you know, uh you can see your long term UM weather prediction and just and then see the app generation. Listen, you can tell like if you're really able to you know, produce that much by end of next year or something like that. So the what the AI is doing is is taking the information, the specific data from individual farmers and combining that with things

like weather data, weather predictions. I'm assuming other information as well and generating a set of recommendations for what would be the most efficient farming choices. Exactly exactly, That's what we are in our building. Yeah, Carla, we're here in part to talk about this women Leaders in AI program that b M is sponsoring. Tell us a little bit about that. What's what are the origins of it, the goals of it, um and how who gets chosen for it. So sketch that out for us. Sure. So first of all,

congratulations to Chimka. She is one of our Women Leaders

in AI honorees. And this program was really created to shine a light on women that are playing a significant role in artificial intelligence and machine learning and and really it boils down to the fact that in order to be it, you have to see it and UH and we want to really give visibility and elevate women like chim Ket and what they're doing today the field, about twenty two percent of the field is made up by women, and in reality it needs to be more in line

with our global population. We'd love to see fIF of the a I community made up of women. And the reason for that is quite obvious. And that diversity of background and and all the ways means diversity of solutions UM and it also means that we build AI algorithms that are free of bias and uh and and some of the traps that can occur when you have too many like minded people working on a solution. How long have has this Women in AI program been running at IBM.

We've been running it for three years now. How does it work? So you either's a kind of slate of grantees every year on how do you get how do you get chosen to be a member of this program? Yes, so we look for remain areas to recognize these women. So we're looking for obviously women that represent diversity in AI who are also looking to highlight progressive examples of how AI and IBM Watson are being applied to business.

And we're curating firsthand examples of people that are pioneers leveraging AI in business and toil because a perfect example that and the way we select them is we're fortunate to have many clients around the world that are using AI and Watson to improve customer experience and gain efficiencies.

And what they've done is helped nominate for us. And in return, what we do is we actually honor the folks that we feel are actually not just making gains in the field, but are actually delivering powerful business results. And uh and we build a cohort. Yea, Kima, do you do you interact with the other people who are winners of the or nominees for the Women Leaders in AI program? Is it a network and learning opportunity in

addition to being an honor Yeah. Of course. In our Aggurly team, three of us are women, and we all got nominated for the honor, and for sure we interact, but also like at the same time, we just we were exposed too many networks, and then we started making connections and started interacting with each other what they're doing and what we are doing, and trying to going to exchange some ideas, like it's usually like on the social

media that we are doing it. So but like, I'm still shocked that I was nominated because like the other nominees are like they're they're such a strong woman, and that's that was just very shocking us. But I'm so happy to be nominated. That actually makes me so happy to hear it because it I didn't realize it was so organic. We call it a cohort, and I thought for sure that it was something formal, But the fact that you all are reaching out to each other makes

me so happy. Okay, I'd like I would always a really dumb question. I was like asking dumb questions. But I'm curious. You know, you you started this caror by saying people in this field are women, and you guys would like it to be more representative of of uh, the actual population. Why is that this is a dumb question. Why is it only Well, I think there's a variety of reasons that you probably know the answer to this better than I do, based on some of the books

you've written, Malcolm. But I think that that we have a lack of pipeline and STEM is an obvious reason. Um. But then I also think there are things like COVID. For example, we lost millions of women in the workforce in the last eighteen months as a result of COVID and the role that women play in many households. So there's a variety of factors at play here beyond just women women entering STEM fields. Um, we're struggling to keep

women in the workforce. Um. But I think what's encouraging to me, and I'm an optimist at heart, is hearing chimkas story. I mean, it didn't sound like chimad that you actually set out to go into a STEM field. It sounds like you're an entrepreneur first and you came into the technology, which for me is super inspiring because that means that the technology is becoming ubiquitous and that you don't actually have to be a person that comes from a science or engineering background to be able to

leverage these tools. What you said, they were two other women in Agerly who are also nominees, So augually seems to have a pretty strong cohort of women at the top. What difference does that make? What do you have an organization that has as many women as that in positions of leadership? Do you do things differently than if you were a company that had entirely man at the top.

I think when we think about arguraally, like our solutions tend to like our plan and resolutions tend to be like more long term and like pretty much detail oriented, you know, like we just see the every risk that could just arise in the long term, and then we just start thinking about like how we can address one by one because usually uh in the startup world, for example, it's very hard to predict like what's going to happen

in the long term. But like for us, actually we always think about like short what's gonna happen in short term, and then we also talk about and then think about more about the long term plan. I think that could be the difference. M hm, Carla, you you are a woman in a field that historically has been very male. I'm just curious over the course of your career, have you what's what kind of transformation in terms of of of representation have you seen in the tech world. Wow,

I've seen a huge shift. In the beginning of my career, I there were many times where I was the only woman in the room, and fast forward to now, I actually feel in most of the rooms that sometimes there are more women than men. And that's something that I hadn't seen in the and in my past. Um. I'll also say, Malcolm, I was interesting this this, I realized this actually today I was speaking to a group of people.

I feel like because of that, I personally have been able to be more of myself um and and It's been this journey to authenticity over the course of my career. And the more I'm surrounded with people like me, the more comfortable I become. Um and UH and it's it's nice to be working with diverse teams. And again it's a big reason of why I chose to come to IBM because there's such a focus on diversity and inclusion.

We had an equal pay policy that predated the Civil Rights Act, for example, and UH and so we've been working on diversity and inclusion initiatives since nineteen eleven. Um, it's kind of mind blowing to think about, and and that's very much a part of who IBM is and what we're about, both internally and externally. When I was fascinated by something you said, which was that you it's much easier to be yourself in environments where so compare your self, Carla to your I don't want to put

a number date on when you started up. So what was it like? I dig into that for a moment. What is the difference between the self you can be now and the self you are when you started out in male dominated environments? I mean I had peers that used to walk the aisles the sales hallways with baseball bats and uh, you know, and swing the baseball bats, um to try and intimidate their sales organizations. You know.

It's it's uh and uh you know, fast forward to here we are during COVID and and people are holding their children while on screen. It's it's just such a juxtaposition. Um. I I grew up in a very formal environment where there were actual dress codes and you can only wear certain things and uh, and so it's it's been a complete and total change that I've witnessed over the last twenty one plus years of my career in tech. Chimka.

Let's let's talk a little bit more about your own personal story and then how you got involved with agrily. So did you grow up in Mongolia? Yeah, I was born and growing up in the Eastern Moss Province in Mongolia. My grandpa she had a small field and greenhouse that we used to just grow up tomato and cumber. It was like back in uh ninety nineties, you know, just like you cannot really find tomato or cucumba very easy

in Mongolia. But m grandma she used to like try to fight against these climate conditions because in Mongolia is the climate is quite extreme. We have like very cold winter, we have like very windy spring, quite chilly autumn, and then also very dry um summer. It could be. I was like always curious about like how people in the rule they are still like going on with white because

most of them are dependent on farming. And then later I think starting into twos and fifteen or sixteen, I started working with this international NGO to fight against human trafficking. I had to travel a lot to the bordering areas and then start training women there who are afflicted with the human trafficking. And it started like telling them what kind of problems they can solve in their rural area.

So that's how I just got into like attracted to maybe I should learn about like more about entrepreneurship, Like I should just change the idea of like starting traditional business like something new, something related to technology or whatever, Like you have to start thinking in a different way, And how did you think in a different way? What was your approach? I found like very common pattern, Like two things I found. The first problem in rural area

was in Mongolia was youth employment. And then second one like a lot of young people struggled to get a job there because there's no job. And second one was like there's nobody in farming, especially young people. They easily give up job in farming. Then I questioned myself why so, like I started talking to the specific smallholder family farmers, like what could be the problems and then what would

be the solutions? And then I thought like maybe those problems can be solved with a smartphone because the users the coverage of the smartphone was quite high. In one boy, everybody has Facebook, everybody has smartphone, so what do you need now? That's what I thought. That's how aggerally idea came up along with my teammates Carla. How how typical is Chimpka and Agrily? Are there a lot of companies

young companies that IBM is working with like that. There are quite a few, and I'm discovering them more and more each day, and it inspires me so much to hear these stories. And I actually see that as one of the primary functions of my role in my organization's role is to to elevate the Chimkas and Agerle's of the world as examples for everyone else to follow. Her story is so inspiring and as actually Chincas you were talking, one of the things I was wondering is what's happened

to the business since you won the award? We have been just piloting the the testing app. The first time we piloted in Mongolia, like in three eastern provinces. We reached out to a lot of farmers who can who are interested in testing this kind of app because this kind of like like mobile app and agriculture sector is

not really common thing. And then everybody was quite impressed because you know, just like there's a young woman just reaching out to people and talking about technology, mobile app and agriculture. I have no idea like agriculture, I have no idea about technology, right, But the only thing is that I knew that there was a real problems that we can solve. Uh. And then we started piloting in Brazil in September, and then in November we started piloting

it in India. So these three countries are like totally different in terms of like how agriculture has advanced. So we started developing like local apps, tailor to Mongolia, tailor to India, tailor to Brazil, and then that's how we started in January, and now we are nearing the launch date in Mongolia and also Brazil and India. We are launching quite soon in the absence of AI. Can you do this without what without piggybacking on Watson and what was that? What would it look like without IBM as

a partner? Impossible or just clunky and not as good. We cannot do anything without those kind of technology. You know that IBM has like the for the weather for example, like we cannot do it by ourselves of course, so like this daily uh, you know just like weekly and monthly, uh, like whether predictions are all from the Weather Company by IBM, and then using our studio we are generating it. We are generating the entire the entire long term forecast for

each cities in different countries. And then also we are using the IBM cloud storage to put everything on the server and then that's how people just can get it through the app. Yeah. Yeah, so hundreds of thousands of developers can leverage these tools to build applications, you know.

And there's another topic which I feel like IBM is starting to establish some thought leadership around, which is not just the tools themselves, with the ethics around the tools and UH and making sure that the algorithms that are being built that then entrepreneurs like Chimka are leveraging the tools for are actually explainable and fair and UH and that that she can be confident in the decision making

of those tools and that they're they're unbiased. And and that requires building algorithms that are that are built on hard evidence like standardized tests and transparent reporting and UM. And this is something that our research team has been very very focused on so that people like Chimka can focus on our business and not have to worry about those components of our tools. And does does the data that you generate Chimpka and we'll be generating over time,

does that get fed back into Watson. Does Watson learn from agrily as well as I really learned from Watson. Yeah, exactly, That's that's what we are doing. So actually, team, we are now working with the IBM open source technology. We are trying to like that, as Carlo said, like you know, we have to have something for free for farmers and then for public that they can use. So we are working with the IBM to uh to have some open source technology which is like basically do this weather and

forum and then also crop risks. We are trying to make it more open source. Like without IBM, like we cannot do it. We cannot just create this such a big network of wordwide and then like you know, just to get a support from the people who are in

the different sectors. So like IBM is basically making it possible. Yeah, we are learning a lot from Watson, and Watson can absolutely learn our data and train itself and then just like you back something really supporting data to like each country in the forming are people that IBM surprised at all the inventive uses that Watson and are being put to. No,

not at all. And in fact, I visited our headquarters for the first time a couple of weeks ago, and it really hit me what IBM has represented in the world in the last hundred years and what has actually come out of this company and and what it is it has enabled. So as an example, our our research team has received five Nobel Prizes. We invented the first

personal computer uh. We invented Lasik, the barcode, the technology behind the A t M, just to name a few very small things that we've invented that have changed the course of how we work and live. So when I think about the future of IBM and the fact that we are building the tools and functionality that will then enable people like Chimpka to create the next set of technologies that will change the way that we work and live, it's not surprising to me because that's part of our heritage.

That's what we've represented and and that's what we're going to represent and enable in the future. So let me ask you, you're we're talking about AI. Have companies like IBM done a good job and explain to the public what AI is all about. Like listening to Chimpka, this is using a technology to solve problems in the lives of an extraordiny number of people who nobody was bringing them that level of technological sophistication and help before. Right,

there's I mean, is that story? Yeah, if I'm being honest, Malcolm, No, it's it's part of it's part of my remit and my organization's role to bring these stories to life. It's part of why we're here with you today, so that

people can learn and what's possible. Um And and and I think that it is our responsibility to to tell these stories so that we can inspire folks to to leverage these technologies to improve our lives and to solve significant problems um whether they're from a business standpoint or from a societal standpoint. And in chim Goes take case, I think she's doing both. Yeah. Why is it hard to tell these kinds of stories? I think there are a

couple of things at play here. I think it's hard to tell these stories because there's so many of them and they're so diverse, and picking the stories that you're going to tell can sometimes be difficult because there's so many different applications. UM. I also think we have a business to run and and there are times where they that we don't actually take the time to explain our technology. There's an assumption because so many people are using it,

but the world already knows what it's doing. But even I myself joining the company, I'm now starting to appreciate how much of the world's backbone, from a technology standpoint, is made up of IBM and UH. And we need to tell these stories to to shepherd this next era for the company, but also quite frankly, to inspire the

next Chimka mm hm. I asked that question about the importance of these kinds of stories because one of the things that struck me with COVID and with you know, this problem of people who are vaccine resistant is I think, on balance, a lot of resistance to vaccines is people can't wrap their mind around the notion that people who do science and technacological innovation are trying to help them. We've gotten so cynical about technology that people assume, oh,

they're doing it, they must have some nefarious motive. There must have been some big bucks involved, There must be and it's not that it's like they actually just want to save your life. And same thing listening to Chimka. You know, I hope you get very rich, chim But the motivation is is you want to help the people back home in Mongolia, right like you you talked about you you started talking about your grandmother for goodness sake,

Like that's your motivation. And I feel like somehow along the way, we we've neglected to inform the world that people who do this, this kind of innovation have the most human of motivations. Yeah, thank you. Purest of intent there, the purest of intent not only in Mongolia, Like I'm gonna apply it, like we're gonna apply it to the whole world, like all emerging markets you will see, Like, thank you. That's wonderful. Thank you. This has been so fun.

I really enjoyed chatting with you, and I, um my hat is off to both of you for telling these kinds of stories. Thank you, thank you so much. Really, thank you, Carla, thank you Morcom. When we see the positive impact made by women in the field, it's obvious that tech companies must become more inclusive to stay innovative. People like Chimka and Carla are driving that impact, using tech solutions to solve problems that most people in the

industry haven't thought of. Thanks again to Carla Pinero, Sublett and Chimka Monk Buyer for talking with me. It was such a pleasure. Smart Talk with IBM is produced by Emily Rosstak with Carl Migliori, edited by Karen Shakerji engineering by Martin Gonzalez, mixed and mastered by Jason Gambrel, music by Grandmasco. Special thanks to Molly Sosha, Andy Kelly, Mia LaBelle, Jacobisberg, Catafane, Eric Sander, and Maggie Taylor, and the teams at eight

Bar and IBM. Smart Talks with IBM is a production of Pushkin Industries and I Heart Media. You can find more episodes at IBM dot com slash smart Talks, and you can find more Pushkin podcasts on the I Heart Radio app, Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell, See you next time.