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Big data for the greater good. To start, I’d like you all to help me with a little exercise - I want you to close your eyes and just picture “data”. That’s right, go ahead, let it wash over you - what do you picture? Well, if you’re like most people, you probably picture
how we decide what products to buy
Why it’s the data scientists! The data engineers! Call them statisticians, analysts, whatever you call them, they’re the people who turn large streams of “big data” into decisions. And the coolest part, the truly coolest part to me, is that they don’t work on data 9-5, they get together and do this in their free time at “hackathons” and coding competitions. I remember being at my first hackathon and thinking this is how we’re going to change the world - I’m sitting next to a guy with a Ph.D. in machine learning, another guy with incredible coding skills, I thought “this is how we’re going to change things - we don’t need our jobs to do this - we’re going to make things that are so important, so world-changing, they’re going to have so much impact! And the things we made were so!
Unfulfilling! Here’s an app to park your car, another to find local deals. These apps are great, but they’re more of the same - apps that make very comfortable lives *ever so slightly* more comfortable. And one of the most exciting things to me about the “big” in big data is that it means “expansive” and that it’s touching everyone, including people like this
clean water NGO. These guys are trying to make the world better every day and, for the first time ever, they are awash in data. Data about surveys they do, about well locations, data about their finances - heck, even if they didn’t collect a single bit of data, groups like the World Bank and the White House are opening data that they could use. So they have this great opportunity to use this new resource of data, just like in the CDC example...
...but they have no one to help them do it. They can’t afford a data scientist, so all that potential gets lost.
So I founded a non-profit called DataKind that connects pro bono data scientists with social organizations. This gives data scientists a chance to have social impact, social organizations a chance to maximize their impact and in the process, we all get to live in a better world. Let me show you a few examples of what this looks like before I close:
Another example comes from the NYC Parks department. They have info about every single tree in the “urban forest” - such a beautiful name for the city’s trees - but they didn’t know the answers to even the most basic questions, namely, when we prune a tree to prevent future disasters, does it help? We suspect it does, but can we use our data to show it?
or, even worse, the anonymous tunnel of binary, like we all read data like we’re int the Matrix or something . And this is sad, I hate to admit that when I hear “data” or “big data” that’s what I picture too, and it’s a shame because data is so much more personal than that. And it doesn’t take much to realize how much big data has touched our lives than to think back to a time before big data, to a time in the dark ages of humanity, back when renting a movie
Jake Porway, DataKind // Data for The Greater Good
Apple iPad mini 2 with
ME279LL/A (16GB, Wi-Fi,
White with Silver)
Amazon - Fire HD - 7" -
8GB - Black
What did we learn about the texters?
Repeat users of crisis
hotlines have been
problematic for all help
centers since the 1970s.
Based on model results,
CTL recalibrated priority of
repeat texters in queue
based on total previous
6 International Chapters