Last week data scientists, researchers, entrepreneurs and analytics experts from around the world gathered in New York City for Bloomberg’s 5th annual Data for Good Exchange (D4GX). Designed to foster conversation and action to solve society’s core problems through data science and human capital, the event gave industry stakeholders an arena to discuss these topics, share challenges, and discuss how they can be overcome through greater collaboration.

This year’s theme was “Our Data for Good?”— or “how data scientists, corporations, policy makers and researchers can collaborate on data science projects that result in positive social outcomes, ensuring that the data science we practice focuses on everyone having a stake, making it solid, fair, and equitable.”

This motif was certainly prevalent in the event’s presentations and conversations. A quick scroll through the event’s Twitter feed, hashtag #D4GX, reveals a passionate and energetic crowd eager to learn, collaborate and share ways to improve our world by applying data science, machine learning and other technical innovations.

One popular workshop focused on how data can be utilized to increase response rates to the U.S. Census. The session’s facilitators believe response rates would improve if people better understood the importance of the Census, and how their input would be put to use. The answer? Working with journalists and other external content creators to increase the prevalence of accurate, relevant and compelling content in internet search results related to the Census.

Another interesting session, led by Andrew Nicklin, the Director of Data Practices at the Center for Government Excellence at John Hopkins University, featured the launch of a new toolkit developed by Nicklin and his team to help governments find and detect bias in their data-driven initiatives. It aims to address the inherent bias that exists in data science by asking participants a series of questions to determine the level or risk involved in a particular data project. Once the risk level has been assessed, specific recommendations are made to help ensure the data is being utilized in an ethical manner.

The Data for Good Exchange also saw companies launch new programs that align with the event’s mission. For example, Foursquare announced its “Foursquare for Good” contest, asking developers and nonprofits for proposals on how its location technology could be used to further a cause and make a meaningful impact.

The event also recognized the work of up and coming researchers with a presentation from recent NYU graduates on using data to “identify, characterize and hold to account New York City’s predatory landlords.”

Eleanor Roosevelt once said, “The future belongs to those who believe in the beauty of their dreams.”

There are countless examples of this beauty in the data science industry, but perhaps the most notable is the sheer volume of people and disciplines committed to harnessing information to make the world a better place. This passion was alive and well at the Data for Good Exchange, and it’s inspiring to think about how the event’s workshops might help shape a more just and inclusive future for all.

To see more, check out D4GX highlight video below: