Positive Disruption:

4 min readJul 30, 2014

DataKind founder Jake Porway wants giving back to be part of data science

By Max Willens

Every second of every day, we are generating and recording information. From the phones in our pockets to the light switches in our homes, everything around us is gathering data and, if used correctly, could help tackle the world’s most pressing problems.

To DataKind founder Jake Porway, this is both an unprecedented opportunity and a transformative shift.

“This is, without hyperbole, a new moment in humankind,” Porway said recently, after a DataKind-hosted panel on the ethics of data science. “Every field is having its data moment.”

Porway also understands that not every field is embracing it. While finance, advertising and web tech companies are running with this data opportunity, the public and nonprofit worlds are struggling get out of the starting blocks. Many have no semblance of the infrastructure (or data architecture) that enables members across an organization to use the data they gather in the course of their work. In fact, at plenty of large nonprofit institutions, years of crucial information is still sitting in filing cabinets, not yet digitized.

That’s where an organization like DataKind comes in. Since its founding in 2011, the Brooklyn-based nonprofit, which is supported by nonprofit and corporate partners like the Alfred P. Sloan Foundation and IBM, has been working with nonprofits and non-governmental organizations to help them make the best use of their data to do better work.

Through work with organizations like the World Bank and New York City Parks Department they’ve helped tackle some of the biggest problems humanity faces — using data scraping to price food more sensibly during crises, or using data sourced from cell phones to figure out where and why a vaccine supply chain was malfunctioning. There’s no set order for problems to tackle — “the north star here is making the world better,” Porway says — but every project shows nonprofits that data can be used by everyone.

“I want these projects to act as examples that say,
‘Yes, you can do this,’” Porway says.

The services DataKind renders are offered by data scientists lending their time and expertise for free. They do it because they want to, and because there aren’t enough data scientists to go around.

“The people who have the skills of statistics and computing are just coincidentally rare,” Porway explains.

“And they cost a lot. The market really drags them to Silicon Valley and Wall Street.”

But the market’s gravitational pull has also created an opportunity for Porway and his team. As data scientists go to finance, ad tech or analytics startups, Porway says they also start yearning for the chance to do something meaningful with their skills.

“Nothing feels worse than realizing you applied that to make a few extra pennies by getting consumers to click an ad for your company,” Porway says.

That’s where his company comes in.

“They can take the same thing they’re doing at their day jobs and apply it to give back, and it makes them feel good,” he says.

But anybody who’s worked in the nonprofit space knows that sparking interest in a cause or an activity is very different from sustaining it. DataKind needs a pool of people who are passionate about helping others in their spare time, and, ideally, it needs that pool to grow, too. That’s why the company regularly hosts meetups that tackle some of the bigger questions surrounding this nascent field.

At a recent event in New York City, about a hundred people gathered for a panel discussion about the ethics of data collection and use. The attendees came from every corner of the tech world — engineers, academics and consultants working in both the public and private sectors.

The panel discussion played out before a full house, which was a positive for Porway. But the fact that half the people at the meeting were new was more exciting to him. At any given meeting, about half the attendees tend to be new, meaning more and more people are being exposed to what DataKind does. And, more broadly, they are being exposed to the idea that pursuing data science should also mean giving back.

“I want to build pro bono into
[data science] from the start,” Porway says.

“Nobody bats an eye at pro bono law,” he continues. “People need these skills and can’t afford them.” But thanks to organizations like DataKind, they may be able to get access to them.