Database Reference
In-Depth Information
statement that we exist as a public good and that our data science solutions
should be aligned with what will make the world a better place and what will
have the most impact on helping the most people.
Gutierrez:
Why should data scientists join forces with DataKind?
Porway:
We want data scientists to volunteer and work with us to have a
tangible impact on the world. There's a great opportunity here to directly
help mission-driven organizations leverage new technologies and the power
of data science to support their work to make the world a better place. In
short, data scientists can apply their skills for good!
This is also an exciting time to be involved in building a Data for Good move-
ment. I really do think people are looking for answers. I hear it all the time
from the social sector: What is data science? How can we use it? Who can
show us the way? DataKind and our volunteers are part of the community
that can start providing answers.
Our projects offer an opportunity to work with real-world data that is hor-
ribly messy—a challenge. This work allows you to face different challenges
than you would face in working with data at a company like Netflix. At Netflix,
they've got a great data architecture in place. They have control of all the
data collected. The difference between the data and how good it is at Netflix
and an organization working to provide clean water to communities in rural
Africa is night and day. The NGO in Africa has probably been recording things
in Excel at best, though more likely on paper, and most likely all of the data
is rolled up across various people's computers and has been input differently.
It's a great challenge to come work on a project where you get to see what
people are really facing in the trenches when it comes to data.
Lastly, another great reason is that you get to make a real impact while doing
something really fun and enlightening. For example, nothing's cooler than walk-
ing away feeling like you found a new use for an old drug through data mining
old medicine databases. Who doesn't want to feel happy about doing good for
the world at the end of the day?
Gutierrez:
When did you realize you wanted to work with data?
Porway:
It was actually a total accident to be honest. I've always been really
interested in artificial intelligence. From a young age, the idea of building think-
ing machines was just fascinating to me. I also really liked problem solving, as
well as being creative. I always thought I was one of those left-brain and right-
brain people. So through a computer, you could combine both halves—you
could create whatever you could dream up.
I took a computer vision course in my last year of my undergraduate degree.
My professor, Shree Nayar from Columbia, one of the best teachers I've ever
had, stood in front of the room and said, “What does it mean to see?” It
became a much more philosophical, even religious, conversation, and I was
