Counter Culture Coffee

Climate change hits hardest where technology is scarcest

This hackathon tackled the real-world problem of climate change impacts on coffee farming using real-world datasets from NOAA & NASA weather data and demographics from Population Explorer. Hosted by The Collider and Counter Culture Coffee, participants were asked to imagine themselves as Guatemalan farmers with limited access to technology and accurate forecasts.

The farmers' entire livelihood is built around productive coffee harvests. Too little precipitation and yields will be low — too much introduces threats like erosion, nutrient leaching, and mold growth. Knowing the forecast is a critical tool for agricultural success.

An additional constraint that sharpened every decision: the target audience had limited access to technology — shared desktops at co-ops and cellular phones restricted to SMS. This pushed the team to dig for low-tech solutions to a massive problem.

A different angle: resilience over prediction

While most teams started honing in on building models to predict future weather patterns, our team focused on predicting precipitation through a wider lens — building resilience. This reframe became the foundation of our entire proposal.

Our proposal

Create a communications system to benefit small-scale coffee farmers in the face of climatic shocks and stressors — collecting and sourcing data and disseminating it as actionable information. Utilizing SMAP & NOAA Seasonal climate forecast data, the system could share soil moisture trends, one-month, and three-month forecasts. Everyone with a phone could participate as "sensors" on the ground, sharing climate observations with one another.

Designing the SMS chat flow

My primary contribution was designing the chatbot flow. For the hackathon demo, the team created a simple forecasting flow — but the "future flow" design showed what a more complex system could look like, where users can request specific information, make reports, and ask questions peer-to-peer.

UX wins the hackathon — and makes a point

I arrived in the morning without a team and felt out of place in a sea of data scientists. By the end of the day, my UX skills had helped bridge the knowledge of my teammates, adding depth and human-centered direction to the project. Our cobbled-together interdisciplinary team won the hackathon.

The team that came in second also had a UX designer on board. It seems that having human-centered approaches brought both projects from raw data to applicable solutions — while many data science-focused teams spent the day sorting through endless climate data without landing on a meaningful deliverable.