How UChicago Is Training Data-Crunching, Do-Gooders Of The Future
Elissa Redmiles had all the background to excel in civic data, but before this summer she didn’t know it.
After receiving an undergraduate degree in computer science at University of Maryland, she worked for a year in curriculum development that encouraged more women to join the computer science field, then worked for a year in marketing at IBM. After two years working in the tech field, but not honing her technical skills, she was searching for a way combine her programming skills and passion for making a difference. Then a friend posted a listing for University of Chicago’s Data Science for Social Good (DSSG) summer program.
“When I saw ‘social good,’ I was like, that is awesome,” she said. “I never see people using technical skills to solve social problems.”
These are exactly the type of people UChicago’s DSSG is hoping to recruit to solve civic problems through big data. The DSSG offers a three-month fellowship where policy researchers, computer scientists, and social scientists use their data skills to solve problems for organizations in need. Since launching in 2013, the organization has grown and evolved both in the type of student it recruits and the projects it tackles, creating more actionable solutions to broader problems.
Redmiles was one of the over 800 students that applied for the DSSG program this year, an increase of over 200 from when the program first launched in 2013. 42 were accepted this summer, and divvied up into small teams to work on projects for partners such as the Environmental Protection Agency, Feeding America, and the Australian Conservation Foundation.
Program director Rayid Ghani, previously the campaign chief data scientist for Obama for America, expected to get applicants who wanted to improve their data skills in a civic setting. As the program evolved, that wasn’t the case. “The response was not what I expected,” he said. “The response was–‘I didn’t realize these problems required the skills that I have.'”
He found that highly skilled statisticians and computer scientists had never been presented with ways their technical skills could be translated to social good, something that is often reinforced by nonprofits and civic organizations that don’t know how to utilize data.
That was the case for Redmiles before she came to DSSG. “I wasn’t entirely sure where my skills would be helpful,” she said. Now she is working with the World Bank to identify fraud in development projects.
The DSSG has also moved to accepting more data-oriented social scientists and policy researchers who can translate data into action– teams are now made up of students from each discipline. Ghani said that will be key to making sure highly skilled students stay in this field. “We want to be sure that anything we do is actionable,” he said. “If you can’t get them passionate or excited about the impact, it just doesn’t work.”
Projects have also evolved and built on top of one another. A graduation rate project for a school district in Montgomery, MD from last year has evolved into a more extensive graduation rate program students are tackling this year. Instead of focusing on the issues that effects education goals at one school, students are looking at how drop out rates compare at schools across the country to understand if there is a more comprehensive solution that is replicable, said Ghani. “Can we now build an open source system that can be used by any school district?” he asked.
Still, there are challenges as the program scales. Right now big data still carries a “big brother” connotation, Ghani admitted. A project that aimed to flag behavioral issues with police officers was nearly put on hold this summer because of privacy concerns in the Charlotte, NC police department (they have since decided to participate). Security is obviously important he said, but he thinks the conversation needs to be reframed as a trade-off. “If you keep everything private and secure, and nobody can see it, then no one can benefit from it,” he said. “It will be completely secure, but completely useless.”
There are other challenges to expansion as they work with nonprofits, government, and other organizations that don’t have previous best data practices in place. Kersten Frailey, a statistics PhD student from Cornell who is working on the graduation rates project said there have been issues parsing through data, as many schools reports disciplinary issues, truancies, and other factors differently. “These are institutions with limited resources and limited human resources, and that definitely makes the levels of inputs very different,” she said.
Ghani anticipates this will change as organizations better understand how data can affect change. Already he has seen partners from previous summers start using solutions across their organizations because they think about data in a different way. “We’re able to not only help them solve that problem, but expand their thinking: what other problems can they solve with their data?”
Via: Google Alert for Data Science