Published by 3BL Media – July 21, 2020
The coronavirus pandemic has amplified the power of data science for social impact in many ways, from helping to deliver school lunch stipends to parents after schools closed to using technology to make accessing critical safety net programs more streamlined and user-friendly. As demand for safety net programs spiked, nonprofit tech organizations stepped up to not only improve access but also to analyze user feedback to identify bottlenecks, speed documentation processes and help applicants find other services for which they’re eligible.
A recent webinar hosted by data.org and the Mastercard Center for Inclusive Growth talked with leading data scientists working for social change about how the pandemic has changed their job and the ethical considerations, data-sharing insights and partnerships needed to ensure data can lead to real change.
Data helps communities respond to COVID-19
Delivering food benefits to out-of-school kids: As schools closed, families who relied on school lunches struggled to feed their children. In response, Congress sought to substitute cash stipends for the subsidized school lunches that nearly 30 million children get each day. Sounds straightforward, but implementation was far from it. “At heart, it is a giant data science problem,” said Tracey Patterson, a senior director at Code for America, which is part of the U.S. Digital Response team providing data experts to governments during the crisis. Code for America has built a digital application for parents that sends a preloaded electronic benefit transfer (EBT) card right to their door.
The problem: Current data management systems aren’t robust enough to keep track of the changing lives of families, particularly in a pandemic when they might be moving in with relatives or sending children to live with other family members while parents work. Even before the pandemic, a surprisingly large number of kids didn’t have a current address on file at school. Code for America and the Digital Response team are looking ahead to the start of the next school year as a critical data collection moment to avoid this problem in the future.