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rayid-techweek

[This post was co-published at the Data Science for Social Good blog]

Last week’s Techweek Chicago event had all the trappings of your typical tech conference. Sprawled out over a floor of the city’s massive Merchandise Mart was a maze of exhibitor booths luring attendees to learn about their new dating service or augmented reality app with tchotchkes and loud music. Three stages offered a full slate of talks and panels about the future of the internet, smartphones and video games, tips for making content go viral and pageant-style battles of aspiring startups. Against this noisy backdrop of buzzwords and brands, the public announcement of the Data Science for Social Good fellowship struck a different note.

Serendipitously following a passionate argument by Jeff Lawson of Twilio for the power of software to change the world, fellowship director Rayid Ghani offered an overview of how the Data Science for Social Good program was designed to fulfill that promise. Inspired by Ghani’s work as chief data scientist with the Obama for America campaign, the vision of the fellowship was to take some of the creative and technical firepower on display at these types of tech gatherings and apply those talents in a new, socially beneficial direction.

“We thought it was really important for people with skills in data and technology to do something useful for a change,” Ghani said. “A lot of work on putting ads in sidebars and optimizing click-throughs or moving money around…there’s nothing wrong with those things, except there’s an opportunity cost. If you’re doing those things, you’re not doing something useful. So we decided it’s time for people who really have the skills to do useful things to really have them do those things.”

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welcome-sign

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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applicant-mapWhile you’re planning for a summer vacation on the beach, we’re planning to host three dozen aspiring data scientists for The Eric and Wendy Schmidt Data Science for Social Good Fellowship. In just a couple weeks, 550 undergraduate and graduate students from around the world applied for the program, as visualized above. While the lucky 6.5% don’t arrive until early next month, the fellowship’s website launched today with portraits and Twitter/GitHub links for all the fellows, mentors and staff involved in this exciting effort. There’s also a debut post on the DSSG blog by organizers Rayid Ghani, Matt Gee and Juan-Pablo Velez, that nicely lays out the grand motivation for organizing this first-of-its-kind program.

By analyzing data from police reports to website clicks to sensor signals, governments are starting to spot problems in real-time and design programs for maximum impact. More nonprofits are measuring whether or not they’re helping people, and experimenting to find interventions that work.

None of this is inevitable, however.

We’re just realizing the potential of using data for social impact. We face hurdles to the widespread adoption of analytics in this space:

  • Most governments and nonprofits simply don’t know what’s possible yet.
  • There are too few data scientists out there – and too many spending their days optimizing ads instead of bettering lives.

To make an impact, we need to show social good organizations the power of data by doing high-impact analytics projects. And we need to expose data scientists to the problems that really matter.

That’s exactly why we’re doing the Eric and Wendy Schmidt Data Science for Social Good summer fellowship at the University of Chicago.

We want to bring three dozen aspiring data scientists to Chicago, and have them work on data science projects with social impact.

Be sure to browse through the fellows and watch the website for frequent updates as the fellowship gets to work this summer. For more on the concept of training data scientists to apply their talents to making the world a better place, read Chicago Magazine’s in-depth interview with Rayid Ghani, posted yesterday.

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ChicagoBlue SmallWatch or listen to the news in any city and you’ll be fed a stream of numbers: traffic times, weather forecasts, sports scores and financial reports. All this data gives a quick, surface snapshot of the city on any given day — what happened last night, what’s happening right now, what will happen over the next 24 hours. But a city’s health is harder to put a figure on, either because of the complexity of data, the scarcity of data or the hiding of data behind locked doors. At the University of Chicago last week, a panel of researchers in medicine and the social sciences discussed how the health numbers of Chicago and other cities can be both collected and applied, enabling research on unprecedented scales and empowering citizens to improve their own wellbeing.

The panel, “Methods, Data, Infrastructure for the Study of Health in Cities,” was part of the broader Health in Cities event, one of four Urban Forums held by the University of Chicago Urban Network encompassing the impressive breadth of city research on campus. Among the participants were several scientists who currently collaborating with CI researchers on how to use computation to better collect, analyze and share data. Kate Cagney, an associate professor of sociology and health studies, is working with the Urban Center for Computation and Data on their efforts to help plan and study the massive new Lakeside development taking shape on Chicago’s South Side. Her team will conduct interviews of residents in the neighborhoods surrounding Lakeside both before and after construction to assess how many aspects of their lives — including health — are affected by this enormous addition to the city’s landscape.

“We have an opportunity to study the impact of building a neighborhood from the ashes,” Cagney said. “New computational and data-intensive science techniques now exist to organize and analyze many disparate data sets, and these will allow for the study of Lakeside in unprecedented detail and produce insights due to real-time data.”

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BigDataWeek-logoLost in the buzz surrounding “Big Data” is the nuance that the phrase can mean very different things according to its context. In the sciences, “Big Data” is a matter of increasing scale for researchers working with massive datasets in physics, astronomy and genomics. In business, “Big Data” offers new ways of marketing to customers or engineering better products and projects. But for a broad segment of the population, “Big Data” has yet to directly impact their daily lives beyond targeted ads on the internet and personalized recommendations for books, music and movies.

In the Computation Institute’s April 25th panel for the international Big Data Week event, three panelists highlighted the potential of this fashionable phrase to make the world a better place. Where data analytics and high-performance computing have long been essential tools in the physical sciences — and more recently in biology and medicine — the crossover of these methods into the social sciences is just starting. Now, as government data becomes more accessible, either publicly or for research purposes, new opportunities to improve the world around us arise, from building more sustainable and healthier cities to protecting society’s most vulnerable citizens from harm.

Charlie Catlett, director of the CI’s Urban Center for Computation and Data, started off the session by urging attendees to “think exponentially” about the world’s problems. Today’s smartphones hold as much computational power as the most advanced, room-sized supercomputers of 25 years ago, Catlett said, illustrating how quickly technology evolves. To maximize the potential of science along this exponential curve, researchers need to aim at problems that may seem insurmountable at present.

“When we’re thinking of a problem or a solution, we’re often overly constrained by what we understand and what we know and what we can do today,” Catlett said. “Where the real creativities and breakthroughs come is when we say, ‘I know I can only do this today, but I also know in five or ten years that the technology will catch up with that vision I have.'”

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Newer, faster supercomputers have allowed scientists to create detailed models of blood flow that help doctors understand what happens at the molecular level. (Photo from Argonne)

Newer, faster supercomputers have allowed scientists to create detailed models of blood flow that help doctors understand what happens at the molecular level. (Photo from Argonne)

This week, some 25 cities around the world are hosting events online and offline as part of Big Data Week, described by its organizers as a “global community and festival of data.” The Chicago portion of the event features several people from the Computation Institute, including two panels on Thursday:  “Data Complexity in the Sciences: The Computation Institute” featuring Ian Foster, Charlie Catlett, Rayid Ghani and Bob George, and  “Science Session with the Open Cloud Consortium” featuring Robert Grossman and his collaborators. Both events are in downtown Chicago, free, and you can register at the above links.

But the CI’s participation in Big Data Week started with two webcast presentations on Tuesday and Wednesday that demonstrated the broad scope of the topic. The biggest data of all is being produced by simulations on the world’s fastest supercomputers, including Argonne’s Mira, the fourth-fastest machine in the world. Mira boasts the ability to 10 quadrillion floating point operations per second, but how do you make sense of the terabytes of data such powerful computation produces on a daily basis?

In his talk “Big Vis,” Joseph Insley of Argonne and the CI explained how he and his team has developed equally impressive visualization technology to keep pace with Mira’s data firehose. Tukey, a 96-node visualization cluster, is Mira’s sidekick, sharing the same software and file systems with its big sibling to more easily take in data and transform it into images. Insley demonstrated how visualization was instrumental in two major simulations conducted on Mira: one studying arterial blood flow and aneurysm rupture in the brain, and another on nothing less than the evolution of the entire universe.

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rayid-ghaniIf you received a surprisingly personalized e-mail or Facebook message from the Obama 2012 campaign, it was likely the product of the campaign’s groundbreaking analytics tools. As chief scientist of that acclaimed team, Rayid Ghani helped bring the computational techniques of data-mining, machine learning and network analysis to the political world, helping the re-election campaign raise funds and get out the vote in powerful new ways. Now that Barack Obama is back in the White House, we are pleased to announce that Ghani is joining the University of Chicago and the Computation Institute. Here, he will shift his attention and expertise to even bigger goals: using data and computation to address complex social problems in education, healthcare, public safety, transportation and energy.

Though he only started on April 1st, Ghani already has a full plate, including a position as Chief Data Scientist at the Urban Center for Computation and Data and a role developing a new data-driven curriculum at the Harris School for Public Policy. But Ghani’s most immediate project is The Eric and Wendy Schmidt Data Science for Social Good Fellowship, which hopes to train and seed a new community of scientists interested in applying statistics, data and programming skills to society’s greatest challenges. We spoke to Ghani about his time with the campaign and plans for the future.

Q: So what brought you to the University of Chicago and the Computation Institute?

Ghani: The reason I got involved with the campaign was that I was looking to combine the things that I care about with the things that I’m good at. I was good at machine learning and data mining research and I cared about making a social impact in the world. The campaign was the beginning of that, but not a long-term plan. After the campaign, I was even more enthusiastic  – if we could do all that we did in a year and a half, there’s certainly a lot more we can do if there is a more focused effort that can last.

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