In terms of sheer unfulfilled promise, interdisciplinary research has to stand as one of the most frustrating examples in the world of social research. The promise can be put simply. The challenges we face in modern society, from responding to climate change through to anti-microbial resistance via so many issues to do with economic, social, political, and cultural well being do not come in disciplinary packages. They are complex and require an integrated response drawing on different levels of enquiry. And yet we persist in organizing ourselves in academic siloes and risk looking like those blind men groping an elephant. As Garry Brewer pithily observed back in 1999, “The world has problems, universities have departments.”
The reasons this promise lies unfulfilled are equally clear. Building an academic career requires immersion in a speciality with outputs (articles, books, talks) that win the approval of peers. Universities are structured in terms of departments, learned societies champion a single discipline, and funding agencies prioritize specific work from those who have built the right kind of credibility in this context. There is, quite literally, a coordination problem here. And this means interdisciplinary work is hard to do well, often falling between stools and sometimes lost in arcane debate about its very nature swapping “inter” for “multi,” “cross,” “trans,” “post,” and other candidate angels to place on the head of this pin.
This isn’t equally true for all disciplines. Some have overcome these hurdles for years—neuroscience, bioinformatics, cybernetics, and biomedical engineering, and more recently we have seen economics taking a behavioral turn while moral philosophy has drawn increasingly on experimental psychology. However, the bulk of the social sciences have proved peculiarly resistant despite how suitable their problem domains are to multi-level inquiry.
The good news is we are seeing substantial shifts in this terrain that could last, triggered in part by the rise of big data and new technology. Social researchers are agog at the chance to listen to millions of voices, observe billions of interactions, and to analyze patterns at a scale never seen before. But to engage seriously requires new methods and forms of collaboration, with a consequent erosion of the once insurmountable barrier between quantitative and qualitative research. An example comes from Berkeley, where Nick Adams and his team are analyzing how violence breaks out in protest movements—an old sociological question, but now with a database (thanks to the number of Occupy movements in the US) that is so large the only way to analyze the material feasibly requires a Crowd Content Analysis Assembly Line (combining crowd sourcing and active machine learning) to code vast corpora of text. This new form of social research, drawing on computational linguistics and computer science to convert large amounts of text into rich data, could lead to insights in a vast array of social and cultural themes of our time.
Moreover these shifts might stick if we continue to see centers of excellence focusing on data intensive social research, like D-Lab at Berkeley or the Institute for Quantitative Social Science at Harvard show how institutions can reconfigure themselves to respond to this opportunity. As Gary King (Director of the latter) has put it:
The social sciences are undergoing a dramatic transformation from studying problems to solving them; from making do with a small number of sparse data sets to analyzing increasing quantities of diverse, highly informative data; from isolated scholars toiling away on their own to larger scale, collaborative, interdisciplinary, lab-style research teams; and from a purely academic pursuit focused inward to having a major impact on public policy, commerce and industry, other academic fields, and some of the major problems that affect individuals and societies.
More structural change will follow these innovations. Universities around the world having long invested in social science infrastructure are looking to these models so as to combine and merge efforts more effectively via multi-disciplinary research centers and collaborative teams. And we are seeing changes in funders’ priorities too. The Wellcome Trust, for instance, now offers the Hub Award to support work that “explores what happens when medicine and health intersect with the arts, humanities and social sciences.”
Of course the biggest shaper of future research comes at a national level. In the UK the proposed implementation of a “cross-disciplinary fund” alongside a new budget to tackle “global challenges” may indicate the Government’s seriousness of interdisciplinary intent. Details will follow, and they may prove devilish. But the groundswell of interest, sustained by opportunities in data intensive research, is undeniable.
So interdisciplinary social research should increasingly become the norm, notwithstanding the fact that specialism will still be important. After all we need good disciplines to do good synthetic work. But if this hope is fulfilled we might see how social sciences could coalesce into a more singular social science and be more fully engaged with problem domains first, and departmental siloes second.