Say hello to Kelsey Meagher! She’s a volunteer with DataKind San Francisco and a Data Ambassador on a project with TechnoServe, an international nonprofit that applies business approaches to help people lift themselves out of poverty around the world. The volunteer team that she’s on is working to develop a tool using machine learning to help TechnoServe improve coffee ripeness with the goal of raising farmer incomes.
Kelsey’s a social scientist and researcher with experience using quantitative and qualitative methods to address complex problems. She holds a PhD in Sociology and is currently a Postdoctoral Researcher in the Department of Food Science & Technology at UC Davis, where she’s leading a research study on how the COVID-19 pandemic has impacted food distribution and hunger relief in California.
To learn more about Kelsey and her journey with TechnoServe in her own words, read on!
Tell us a little bit about yourself and your background.
I’m a sociologist by training, and my research focuses on food and agriculture systems, public health, and social inequality. Currently, I work in the Department of Food Science and Technology at UC Davis. I’m a mixed-method researcher, which means I combine quantitative and qualitative methods in my work. I joined DataKind San Francisco last year, and I’ve loved the opportunity to work with incredible data scientists and nonprofit partners on high-impact projects.
Can you briefly describe the project that you’re working on?
My team and I are working with TechnoServe to develop a machine learning algorithm to classify the ripeness of coffee cherries from images taken at wet mills in Latin America and Africa (where raw coffee cherries are processed). The goal is to develop a tool that will help TechnoServe standardize quality assurance at their wet mills and work with farmers to improve coffee ripeness. The market price for coffee is largely determined by ripeness, so our goal is to raise farmer incomes by improving it. Our team is still in the design phase of the project, but we’re excited about our preliminary results.
What surprised you most about this project so far?
I’ve learned so much about coffee production! Recently, TechnoServe took us on a virtual tour of a wet mill in Guatemala and showed us the entire process of receiving and processing coffee cherries. We learned about regional differences in coffee production across Latin America and Africa, which has been critical for our scoping process. Since our goal is to develop a tool that TechnoServe can deploy to their numerous partner sites around the world, it was important for us to understand the different contexts in which our work will be used.
What is the highlight of the project so far?
I’ve really enjoyed the opportunity to learn new skills through this project! As a social scientist, I haven’t had much experience analyzing images; most of my research has involved tabular data or unstructured, textual data. I feel fortunate that my team includes people with diverse backgrounds who have taught me a lot about computer vision, image segmentation, and deep learning.
What advice would you like to share with volunteers who are new to DataKind or the Data for Good movement?
My advice would be to take the time to understand your nonprofit partner’s mission and operations. Our work often involves projects where we might have little to no domain expertise, and every nonprofit has unique operational constraints. It’s important to develop a deep understanding of our partners so we can deliver tools and insights that truly address their needs – even if that involves implementing lower-tech solutions with tools we may not prefer.
How did this project introduce you to new connections/friends?
In a year that’s been difficult to meet new people, I’ve been grateful to make so many valuable connections through this project – from my fellow DataKind Data Ambassadors in San Francisco and Washington, DC, to our TechnoServe partners in Africa and Latin America. I feel lucky to collaborate with such kind and passionate people.
What does “living with a sense of purpose” mean to you?
I’ve never been the kind of person who feels a singular sense of purpose; my goals have changed over time as I’ve matured and my circumstances have shifted. That said, I try to approach new opportunities by looking for an alignment between my skills and values. I try to live in such a way that my impact on this planet is net positive.
Who inspires you?
Lots of people inspire me! These days, I’m inspired by all the people who are working so hard to care for their communities during the pandemic. This has been a tough year, and I’m grateful for everyone working to ensure that the most vulnerable among us receive care and support.
What’s the last book you read?
I just finished “The Broken Earth” trilogy by N. K. Jemisin, which I really enjoyed. Currently, I’m reading “Algorithms of Oppression” by Safiya Umoja Noble.
About Volunteer Spotlights
Our volunteers are the lifeblood of our mission. They’ve inspired people to use their skills in ways they never dreamed of. They’ve slayed misconceptions. They’ve shown organizations trying to make the world a more humane place how data science and AI can change the game. We’re honored (and thrilled) to feature their stories in DataKind’s Volunteer Spotlight series. Follow this series to learn about their impeccable skill sets, their work with our brilliant project partners, and what inspires them to give their time, resources, and energy to causes that matter.
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