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But the projects—they're actually Trojan horses to this greater movement.
We see the mix of project work and our global chapter network as a way to
help mission-driven organizations realize the power of data science in their
work—and ultimately enhance data literacy in the social sector. So we've had
tons of groups coming in saying, “I don't know what this is,” and walking
out saying, “Oh, I see how data science could help me and my organization.”
Once they see the power that data science can lend to their efforts to achieving
their mission, advocating for a cause, or working with communities, they have
the ammunition they need to make the business case for their organization to
invest in data science professionals.
There's a flip side to this too. I also think that pro bono service should be built
into the data science profession as it is being established. People sometimes
ask us, “Why would a data scientist who makes six figures volunteer to do
good?” However, no one bats an eye at pro bono legal work. It's just a part of
the profession. So I think that by creating an opportunity for professional data
scientists to give back and see the impact that their skillset can have on some
of the most pressing issues we face allows us to set the stage for companies
and others to make this a part of how we all do business. Data scientists in the
business world are all generally well-compensated. Let's give back.
Gutierrez: You were at The New York Times and then you decided to start a
nonprofit. Why the change in focus and why was a nonprofit the right vehicle
for your goals?
Porway: For me, what it really came down to was—and this is going to sound
corny—this has always been a dream job for me. I always wanted to find ways
to use my skills for good. I had this feeling that I needed to give back. However,
every time I got out of school with a degree—I started with computer sci-
ence and later with statistics—most of the jobs available were not particularly
socially fulfilling. I had bills to pay and it was very hard to find those fulfilling
gigs that could pay those bills. This work did both. I just didn't actually expect
it to come along this way. I could have gone and tried to work for Amnesty
International, but it just turned out that there were other data scientists
out there who wanted to do this too and so we got together and said let's
build this right now. Now is the time, and everyone else is interested. This
is more than me. This is a movement.
As to your other question about establishing DataKind as a nonprofit, we did
so because we didn't want people questioning our motivations for solving
problems and our goals. The work we do is so sensitive, because we're han-
dling people's data and because we're getting out there to do good with that
data. If we were a for-profit, I'd be very concerned that people would always
wonder what our motivations were for doing things. Would we end up taking
the higher-paying projects over the projects that would make a bigger differ-
ence? And so establishing DataKind as a nonprofit was a very loud and clear
 
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