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Historians May Never Rule the World, but Their Models will Rule the Data-Driven Future

Historians once told arching stories of scale. From Gibbon, Mommsen and Fustel de Coulanges on the tides of ancient institutions, and Macaulay and Michelet on the making of modern nations, to Mumford and Schlesinger on modern cities, historians dealt with long-term visions of the past over centuries or even millennia. 

Nearly forty years ago, though, this stopped. From about 1975, many (if not most) historians conducted their studies on much shorter time-scales, usually between five and fifty years. This compression of time in historical work can be illustrated bluntly by the average number of years covered by doctoral dissertations in history conducted since 1885 in the US. In 1900, the period was about 75 years; by 1975, it was closer to 30. Command of archives, total control of a ballooning historiography and an imperative to reconstruct and analyse in ever-finer detail had become the hallmarks of historical professionalism.  Grand grand narratives became increasingly frowned upon.

Two thousand years since Cicero minted the phrase historia magistra vitae – usually translated as history is life’s teacher – the ancient goal for history to be the guide to public life had collapsed. As Harvard historian Daniel Lord Smail wrote in a 2011 article in French Historical Studies, the “telescoping of historical time … the discipline of history, in a peculiar way, ceased to be historical.” At the same time, history departments lay increasingly exposed to new and unsettling challenges: the recurrent crises of the humanities, marked by waning enrollments; ever more invasive demands from administrators and their political paymasters to demonstrate “impact”; and internal crises of confidence about their relevance amid the emergence of new disciplines such as political science, which were enjoying swelling classrooms, greater visibility and more obvious influence in the shaping of public opinion.

So professional historians ceded the task of synthesizing historical knowledge to unaccredited writers – and simultaneously lost whatever influence they might once have had over policy – to colleagues in the social sciences: most spectacularly to the economists. This narrowing of vision reflected the turn from long-term to short-term thinking in culture at large that took place in the 1980s. Few politicians planned beyond their next bid for election and companies rarely looked beyond the next quarterly cycle. The phenomenon even received a name – “short-termism” – the use of which sky-rocketed in the late 1980s and 1990s. It has few defenders, but short-termism is now so deeply ingrained in our institutions that it has become a habit—much complained about but not often diagnosed. 

Yet there are signs that the long-term and the long-range are returning. The scope of doctoral dissertations in history is widening again. Professional historians are once again writing monographs covering periods of 200 to 2,000 years, or even more. And there is an expanding universe of historical horizons, from the “deep history” of the human past, stretching over 40,000 years, to “big history” going back 13.8 billion years to the Big Bang. 

One reason for this shift has been the rise during the last decade of big data applied to problems of vast scale such as climate change, international governance, and inequality. Big data have frequently been used to suggest that we are locked into our history, our path dependent on larger structures that arrived before we got here. For example, "On the Origins of Gender Roles: Women and the Plough," a recent article in the Quarterly Journal of Economics, tells us that modern gender roles have structured our genes and our preferences since the institution of agriculture. A paper in the American economic journal Macroeconomics asks: “Was the Wealth of Nations Determined in 1000 BC?” And evolutionary biology has also seen an abundance of data being interpreted according to one or two hypotheses about human agency and utility.

The arbitration of data is a task in which the history departments of major research universities will almost certainly take a lead since it requires talents and training which no other discipline possesses. Historians are trained to synthesize the various data even when they come from radically different sources and times. They are adept at noticing institutional bias in the data, thinking about where data comes from, comparing data of different kinds, resisting the powerful beckoning of received mythology and understanding that there are different kinds of causation. 

As well as writing critical long-term perspectives on the issues of climate change, governance and inequality, historians are becoming the designers of tools for analysing data. For instance, one of us, Jo Guldi, has co-designed a toolkit called Paper Machines for aggregating and analyzing large numbers of documents. Developed with ethnomusicologist Christopher Johnson-Roberson, it allows scholars to track the rise and fall of textual themes over decades, allowing them to generalize about wide bodies of thought, such as things historians have said in a particular journal. This facilitates the construction of hypotheses about longue-durée patterns in the influence of ideas, individuals and professional cohorts.

The future training of researchers across a wide range of disciplines should be based around the interrogation of big data – such as that relating to era, gender, race and class - in search of turning points and processes that take a long time to unfold. And the expertise of historians in curating and critiquing statistics, expertise and professionalism among other communities makes them ideally suited to be the arbiters of the information. Armed with critical transnational and transtemporal perspectives, they can be the public’s guardians against parochial, self-serving perspectives and endemic short-termism.