Archive for June, 2013


As the Eric & Wendy Schmidt Data Science for Social Good fellowship enters its third week, the orientation ice-breakers of the first couple days have given way to the grind of hard work. Following the technically-oriented “boot camp” of the first week, where fellows got a crash course in the software and tools at their disposal this summer, the second week featured a different sort of educational experience. A steady stream of experts, on topics ranging from Chicago crime and public transit to energy infrastructure and early childhood interventions, visited the DSSG space to expose fellows to the gritty details of the real world problems they will address.

The purpose of these visits is for the fellows to learn about “the dark matter of public policy data,” the important information that won’t necessarily show up in the numbers that they’ll work with during their projects. Some of the speakers chose to give the fellows a little dose of humility, such as Paul O’Connor from architecture firm Skidmore, Owings & Merrill, who challenged them with the questions of “Who are you, and what are you looking for?” amid a history lesson on Chicago.


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Forest of synthetic pyramidal dendrites grown using Cajal's laws of neuronal branching (Wikimedia Commons)

Forest of synthetic pyramidal dendrites grown using Cajal’s laws of neuronal branching (Wikimedia Commons)

Trauma surgeons know how to fix gunshot wounds, lacerations and broken bones. It’s what comes afterwards that really worries them. Even after the initial injury is treated, patients are at risk for secondary issues such as infection, sepsis and organ failure. While the biological pathways involved in these processes have been well studied and characterized, effective interventions to reliably stop the dangerous cascade have yet to be discovered.

“It was very frustrating for me to not have the drugs and tools necessary to fix what I thought was actually going wrong with those patients,” said trauma surgeon and CI senior fellow Gary An, in his University of Chicago Alumni Weekend UnCommon Core talk. “Often we know what will happen, but we have no way to stop it.”

The current fashionable approach to such intractable problems in medicine and other fields is Big Data, where answers hiding in massive datasets will be uncovered by advanced analytic methods. But quoting Admiral Ackbar, An warned the audience that this approach alone “is a trap,” generating a multitude of correlations and hypotheses that don’t always translate into real world applications.

“What it wants to appeal to is magic…if you can get enough data and a big powerful computer, an answer will magically appear,” said An, an associate professor of surgery at University of Chicago Medicine. “That’s fine if you want to diagnose or characterize. But if we want to engineer interventions to be able to manipulate systems, we need to have presumptions of mechanistic causality; we need to be able to test hypotheses.”


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The Data Science for Social Good summer fellowship is officially underway, as (most of) the 36 fellows have made it to Chicago, met their mentors and explored their new digs on the Chicago River. Juan-Pablo Velez captured the excitement of the first day over at the fellowship’s blog, where there will be plenty of updates all summer.

We spent our first day getting to know the program, and each other.

Program director Rayid Ghani kicked things off by welcoming mentors, staff, and fellows.

“Three months ago, we didn’t know we were doing this. Lots of people did a ton of work to get you here,” Ghani said. “But this is now your program – it’s up to you to make this work.”

“No pressure.”

Details of the projects our crew of data scientists will be tackling this summer will be announced later this week.

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