In a small classroom at University of Chicago's Harris School of Public Policy on a balmy fall evening, Brett Goldstein laid out the next two years to a group of 20 future civic data scientists.
"People go in feeling like they have to change the whole thing," he said, of getting into the civic data space. "Just shifting the dial a few inches matters too."
It was an orientation meeting for this year's cohort in the masters in Computational Analysis and Public Policy (CAPP) program at Harris. The program, which started last year, gives equal weight to developing computer science skills to handle large influx of civic data, and the thought process behind how that translates to civics. It's for the data scientist who sees Python as policy. Or the researcher who wants to make massive data sets matter in the real world.
Part of it is understanding that the road to civic data success often takes a circuitous route, and a multidisciplinary approach. At this meeting Goldstein detailed his journey from IT guy to Chief Data Officer of the city of Chicago. His talk traced the unique journey of one data scientist, answered questions about what students can expect in the program, and gave a peek at how data science is evolving with the influx of urban data.
Goldstein certainly had an interesting road to his role as a fellow as senior fellow at UChicago's Harris School. He was working in IT when he got a call from his friend Chuck Templeton, who wanted him to help him build a little company called Open Table. For seven years, Goldstein oversaw the technical development of one of the earliest tech successes, and got his masters in computer science at the University of Chicago.
A few years into working at Open Table, 9/11 happened. In the ensuing days, watching stories of firefighters, police officers, first responders, and others rush in to help those in the wake of a violent tragedy, Goldstein had an epiphany of sorts. It was time to do something a little different. "What do I do? I make restaurant reservations easy," he remembers thinking at the time.
So he took the police test. In July of 2006, he was accepted to the police academy. After nearly a decade of running a tech startup and studying computer science, he decided to become a beat cop.
Goldstein graduated at the top of his class and chose to serve on the West Side of Chicago, an experience that really gave the "ground truth" to policing, something he had previously pondered while studying at UChicago. It was a rough neighborhood, and he found himself face to face with the harsh realities of Chicago's underserved neighborhoods, responding to murders, drug deals, domestic abuse, often within the same shift. After that experience, "you can no longer be a passerby," he said.
After about 10 months on the job, he was transferred to the main offices to put his computer science degree to use cracking data challenges in crime statistics. His theory was that crime wasn't a simple case of reported activity--it was a multidisciplinary problem due to a complex layers of issues. So he worked on creating predictive analytics, which could take disparate stats, including liquor licenses, potholes, and 911 calls, for example to predict a where a crime was likely to happen. His thoughtful, data driven approach to policing caught the eye of Rahm Emanuel, who asked him to be the Chief Data Officer of the city when Emanuel was elected Mayor. From there, Goldstein brought huge quantities of data to the city's open data portal, and later created the Windy City Grid, a real time city management platform.
No one's asking these students to take that sort of route (the fact that Goldstein and other did it this way paves the way for a clearer road to civic data work), but the curriculum does offer opportunities to blend on-the-ground experience with data crunching. Students take intensive computer science courses and study policy creation, and different types of databases. There's overlap with other big data civic projects at UChicago: Rayid Ghani, head of the Data Science For Social Good Fellowship, is teaching machine learning for public policy next spring.
The background of students is diverse, but drawn together by curiosity and desire to change and build off of previous experience. Students such as Emily Webber, who came to the program after several years of working in nonprofits and teaching herself to code. This offered a chance to bring together data and social science in a way she hadn't seen before. "It just made sense," she said.
"We needed a new type of person to come into politics," Goldstein said, referring to when he started with the city of Chicago. Someone with a combination of tech, policy, and statistics that can capture the incoming tidal wave of urban data and turn it into something good, he added. There's a room full of them at UChicago.
Image credit: Wikimedia
