Today, a tiny office in the sprawling edifice of the National Institutes of Health released a strategic plan. The 58-page document, complete with bullet points and clip art, spells out a direction for behavioral and social science research--including psychology, economics, and sociology--for the next four years. And while it doesn't directly shunt funding around, the plan is a bat signal for social scientists across the nation: It shows what the NIH is interested in and (likely) where grants will follow. And that could ultimately shape the direction of behavioral and social science itself. The plan comes from the Office of Behavioral and Social Science Research, an arm of the NIH that directs social science efforts within each of the agency's 27 institutes.
This viewpoint is about differences between computer science and social science, and their implications for computational social science. Spoiler alert: The punchline is simple. Despite all the hype, machine learning is not a be-all and end-all solution. We still need social scientists if we are going to use machine learning to study social phenomena in a responsible and ethical manner. I am a machine learning researcher by training.
The advent and popularity of online social media also allows the creation of massive data sets which can inform models and underlying sociological theory. The ubiquity of smart devices (such as smart phones) also provides opportunities to gather extensive data on the behaviors and interactions of humans in real space. The goal of this symposium is to bring together a community of researchers interested in addressing these issues and to encourage interdisciplinary approaches to these problems.