This document discusses the role of humans in analyzing big data, noting that while data is abundant, humans are needed to make sense of patterns and provide useful insights. It introduces Lola Chen, who is able to identify patterns of pothole problems across Chicago streets through close observation, whereas analyzing large amounts of road data would take much longer. The document lists the contributors and software used to create it.
9. “Any alert person can
ride the streets of Chicago
and see the pattern
of pothole problems.
The ride might take
4 hours or so.
The making notes might
take 1 hour.”
20. • Advisor: Monica Ramirez
• Technical Support: Jazmin
• Interviews:
– Gary, Jazmin, Monica: USA
– Alex: France
– Henri: London
– Saud: Saudi Arabia
• Photos
– Lola by Julian Crespo
– Potholes by Lola Chen
• Software: PhotoGrid, Cute Avatar, Pages
Editor's Notes
I’m Dan O’Neil, and I run the Smart Chicago Collaborative, a civic organization devoted to improving lives in Chicago through technology. I’m here with Lola Chen, a community advocate here in Chicago. We are going to talk about the role of humans in predictive analytics in an urban environment.
I think it has a great role to play in helping understand how to run a city. The understanding of facts is critical to a just society. And what makes sense for other segments of our culture and economy can make sense for government.
And much of my career has been devoted to data. I’ve made data-driven web products for the last decade. Smart Chicago Collaborative is a national leader in the creation of civic apps. We were the impetus behind bringing Open 311 to Chicago. I guess the point is, I know of what I speak.
In my work at Smart Chicago, I’ve come to deeply appreciate the value of humans. They make all data. Data is a subset of humanity, not the other way around. I’ve seen first-hand what happens when the fetish of data can make everything go wrong.
So I am dubious of any discipline that seeks to help people that doesn’t seem to really include people in meaningful ways. Remember how stoked Burgess Meredith was in the Twilight Zone when all the people were gone and he was left with his books?
Pretty much every time I see something in the world of “big data” or “predictive analytics”, there is never any mention of humans. As if the machines are autochthonous, indigenous, comes from nowhere and knows everything. Empty of humans.
But of course humans have made everything. And they are the most versatile and capable objects on earth. Burgess Meredith got pretty bummed when he immediately broke his glasses and couldn’t read any of his glorious books. His myriad word repositories were of no use. If only there was one other human left to read to him.
I’ve come to know Lola through the OpenGovChicago meetup and she’s helped me greatly in my work at Smart Chicago. She is an amazing Chicago resident. She values data and technology, and is one of the best humans I know.
Lola Chen is the master of the email. As I was preparing for this event, and I was pondering the value of humans in big data, she wrote me one of her missives. In it, she wrote, “Any alert person can ride the streets of Chicago and see the pattern of pothole problems. The ride might take 4 hours or so. The making notes might take 1 hour.” This is what I mean. This is the value of humans. So I yield the remainder of my Pecha Kucha to the great Lola Chen.