Taking research to policy is our thing; social science is a means to that, not an end. Yet, we cannot help but think of how weak an instrument social science has become, especially in South Asia.

Here is something I wrote in relation to some internal discussions a few months back:

Expressed demand for social science may be difficult to demonstrate, but there can be little doubt that social science is critically important for informed policy making and implementation. As evidence-based policy making receives greater acceptance, demand will increase for high-quality social science graduates or for repurposing of graduates from other fields.

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Increasingly, the “attention economy” is becoming more important than industrial and agricultural production per se, even in developing economies. Control of economic and social processes assumes a high priority, including control of consumer behavior. This leads to the pervasive spread of the data economy, seen in the media and in the public imagination as an increased reliance on big data. It is not that big data and business analytics started in the past few years. But they have entered public discourse because changes in computer storage and software have “democratized” the analysis of large volumes of high-velocity, complex and variable data that were hitherto analyzed by large companies and governments who could deploy supercomputers.

Big data require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information. The term can be used to describe data generated as a by-product of doing things (such as providing telephone service, processing payments, and so on), but it also covers large volumes of content produced for specific purposes (such as digitized text, video/ audio, tweets, Facebook status updates, etc.).
Large claims have been made for big data. Some of the claims have been overblown. But the potential exists for a new kind of social science that has big data at the center and aggressively melds the potential of computer science with sophisticated understandings of social theory and methods. Given the relative weakness of social science in South Asia (and elsewhere) vis-à-vis computer science, the outcome of big data research is likely to be atheoretical and fragmentary. What is proposed is the building of a research program at the intersection of data and social sciences. It will break the silos that have grown too powerful within conventional universities. It will be ideally positioned to realize the potential of the emerging trends in economies and societies.

This resonates with an op-ed published in the NYT by the Co-Director of the Yale Institute for Network Sciences:

So social scientists should devote a small palace guard to settled subjects and redeploy most of their forces to new fields like social neuroscience, behavioral economics, evolutionary psychology and social epigenetics, most of which, not coincidentally, lie at the intersection of the natural and social sciences. Behavioral economics, for example, has used psychology to radically reshape classical economics.

Such interdisciplinary efforts are also generating practical insights about fundamental problems like chronic illness, energy conservation, pandemic disease, intergenerational poverty and market panics. For example, a better understanding of the structure and function of human social networks is helping us understand which individuals within social systems have an outsize impact when it comes to the spread of germs or the spread of ideas. As a result, we now have at our disposal new ways to accelerate the adoption of desirable practices as diverse as vaccination in rural villages and seat-belt use among urban schoolchildren.