Steven Mornelli thinks it's time to cut through the hype surrounding big-data. That's why he and three of his colleagues formed The NYC Data Skeptics Meetup, a new group designed to examine the mathematical, ethical, and business aspects of data from a skeptical perspective. It will meet for the first time in Manhattan on June 19.
Mornelli is executive vice president of consulting and data science services at Johnson Research Labs (JRL) -- a New York City-based startup where a small group of data scientists, social scientists, and cloud computing experts are combining technical training in data science with practical business experience to gain insight from big-data. He organized the Data Skeptics group with the help of three associates: JRL co-founder David Park, and senior researchers Cathy O'Neil and Rachel Schutt, co-authors of Doing Data Science.
A lot of people claim big-data can solve the world's business and social problems, large and small, Mornelli explained in an email interview with me. How accurate or misleading is this message -- and what opportunities exist for those who are willing to examine the larger issues with a skeptical view? He wrote:
I want to bring together alternative views that can lead to interesting (and at times exasperating) dialog between participants who may reside in one of two groups -- those on the data science side versus those on the business side. These two groups need to learn each others' language, needs, and ways of thinking to make change happen.
Mornelli worked for many years as a consultant in the field of mechanical system simulation, and later, quantitative research. "I had the distinct pleasure of working with some of the most brilliant colleagues of my career," including engineers, mathematicians, physicists, computer scientists, and others. He continued:
I went on to pursue less data-intensive jobs but never lost my passion for deep analytics and first-hand knowledge of the impact that a well-managed, excited, and dedicated group of technology nerds can make -– in their own lives, the community, and society at large. I view the explosion in the field of data science (and big-data) as an opportunity to make a real difference on a larger scale.
While it may seem counterproductive for someone with a passion for analytics to pop holes in the big-data bubble, Mornelli said he thinks just the opposite is true: "...the credibility and opportunity of big-data can be derailed if true business insights are not achieved and organizations fail to make use of them. The best analytical results mean nothing if company leadership cannot interpret them."
Mornelli's goal is to examine ways that data and modeling can be used in the wrong way -- either intentionally or not.
No one seems to be focusing on this topic as everyone wants to jump on the bandwagon. Over time, I've become more skeptical when viewing the use of data and models. I'd like to see great debate that allows us to discern the key factors of success behind successful examples of big data and advanced analysis.
The new group would feature guest speakers from diverse fields -- from politics and economics to healthcare and non-profits, he said. "To give an example, our first speaker will discuss the misuse of 'political data' and how data science might be getting used in authoritarian countries."
Since it was announced early this month, The NYC Data Skeptics Meetup has attracted more than 330 members -- data scientists, students, mathematicians, analysts, and data engineers.
How important do you think it is to critically examine big-data and its implications? Is it time to find the realities hidden in the hype? Share your opinions below and take our "Bursting the Bubble..." quick poll, at right.