Data Science at Columbia: Data for Good
Every field has data. We use data to discover new knowledge, to interpret the world, to make decisions, and even to predict the future. The recent convergence of big data, cloud computing, and novel machine learning algorithms and statistical methods is causing an explosive interest in data science and its applicability to all fields. This convergence has already enabled the automation of some tasks that better human performance. The innovations we derive from data science will drive our cars, treat disease, and keep us safe. At the same time, such capabilities risk leading to biased, inappropriate, or unintended action. The design of data science solutions requires both excellence in the fundamentals of the field and expertise to develop applications that meet human challenges without creating even greater risk.
At Columbia University, we use the tagline “Data for Good” to capture succinctly the who, what, when, why, and how of data science at the university. In this series of posts, I will elaborate on what “Data for Good” means and how we at Columbia promote this mission.
Jeannette M. Wing is the Data Science Institute's Director, and professor of computer science at Columbia University. For more data commentary and analysis, visit datascience.columbia.edu/voices.