Years ago, when they decided to launch a conference focused on data, the team at global information and tech company Bloomberg wanted to do more than focus on how data can improve operating efficiencies and boost revenues. They wanted to explore how data science methods and modern machine learning can be applied to solve humanitarian issues and give back to society at large. Maybe something for associations to be inspired from?
Introduced in 2014 as part of the 20thACM SIGKDD Conference on Knowledge Discovery and Data Mining in New York City and expanded to a standalone event the following year, the Data for Good Exchange has doubled its attendance in just five years. And for last year’s meeting in Bloomberg’s New York City headquarters, even more people wanted to attend but couldn’t: registration filled to the event’s 1,000-attendee cap just three days after opening.
From the beginning, “we felt that [this meeting] really filled a void,” said Victoria Cerullo, conference lead for the 2018 D4GX, shorthand for the Data for Good Exchange. Before Bloomberg created the Data for Good Exchange, she said, “there really wasn’t a forum for data for good to be discussed to the extent that it is at our conference.”Bloomberg’s Data for Good Exchange website page describes its mission this way: “The forum enables participants to build cross-sector relationships while solving problems for the social good that might not otherwise be addressed by market forces.”
This year, the single-day event tackled issues ranging from gender equality and climate change to human genetics and the U.S. census — all through the lens of data science. Its audience included researchers, academics, nonprofit leaders, policymakers, and data scientists who come mostly from the U.S., but also flew in from South America, Europe, and Asia. Some attendees work with data every day. Others “know that data is important,” Cerullo said, “and just want to understand how it can help them.”
Putting Feedback Data Into Practice
The Data for Good Exchange is still a relatively young conference, so organizers continue to tweak, refine — and sometimes significantly expand — its programming each year to better serve their diverse audience.
“Attendees said there was great content, great information, but — particularly the data scientists — said they really wanted to roll up their sleeves and do something concrete,” Cerullo said. As a result, this year’s program included a handful of workshops, which were designed to spark discussions and help attendees develop fresh ideas for tackling major challenges.
The conference was divided into four workshops focused on data in varied sectors. One group discussed how governments can find and detect bias in their data-driven initiatives; another, how media can help increase census-response rates. A third workshop talked about encouraging collaboration across sectors in the “data for good movement.” The fourth focused on using data to help communities in need.
“We could only have about 50 people in each workshop, but there was so much demand for them, there were lines out the door,” Cerullo said. “That told us that this is something our attendees are really interested in and engaged in.” This led to another idea: since relatively few attendees could attend each workshop, the conference offered an end-of-day “workshop takeaways” panel, which allowed everyone to hear what the workshop participants had discussed.
Cerullo said that graduate students are a significant part of D4GX, and their work takes center stage in one of her personal favorite conference elements, the immersion program. Via a partnership with NYC Media Lab — a consortium of New York City-based universities and the city’s economic development corporation — the program offers a stipend to several doctoral students who study data science or statistics and sends them off to help nonprofits solve real-life data challenges. Then the students appear on a panel at the conference — alongside representatives from the nonprofits they assisted — to discuss those challenges and how they approached them.
This year, one pair of students helped a nonprofit in the Virgin Islands with its post-Hurricane Maria population survey. Another student worked with the Billion Oyster Project, which aims to restore the oyster population around New York Harbor, and a third helped the city of Milan better manage its data. “Students have always told me that they really value this because they’re typically sitting in front of screens, looking at lots of data on their day-to-day spreadsheets,” Cerullo said. “To be able to connect that with something on the ground is just so valuable.”
This article, excerpted and modified for Boardroom, is part of a special content-sharing agreement Boardroom has with Convene, the PCMA magazine. Contributing editor Molly Petrilla is a New Jersey–based freelance writer for Convene. The full version of Molly’s story is available in the February edition of Boardroom.