Order of Multitudes

Collaboration Across Boundaries: Chatting with Deborah Coen About Crossing Disciplines

Deborah R. Coen is a Professor in the Department of History and Chair of the Program in History of Science and Medicine at Yale University. She is the author of three books: Vienna in the Age of Uncertainty: Science, Liberalism, and Private Life (2007), The Earthquake Observers: Disaster Science from Lisbon to Richter (2013), and most recently Climate in Motion: Science, Empire, and the Problem of Scale (2018), which won the Pfizer Award from the History of Science Society in recognition of an outstanding book in the history of science. Professor Coen and I recently sat down to talk about her research and participation in the Sawyer Seminar.

Sarah Pickman: Tell me a bit about your academic background and research interests.

Deborah Coen: My background is in physics and history of science, with a geographic focus on modern central Europe, mostly in the nineteenth century. I’ve spent a lot of time over the past decade or so studying the history of the science of climate. Over the past couple of years that has included recent climate science, but much of my research has concerned climate science before 1900, before the age of computers and satellites. One of the themes running through my research projects has been the role of non-expert observers in producing, and even interpreting, data in the sciences.

SP: Can you speak briefly about how the Sawyer Seminar began to take shape? What were the intellectual ideas that formed the seeds of this project?

DC: The story behind the Sawyer Seminar starts with a conversation that Ayesha Ramachandran, Marta Figlerowicz, and I had in December of 2017, I think, about the parallel developments in our fields around the turn to “the global.” My own discipline has been trying to conceive of what a global history of science would look like, and it turns out that literary scholars have been rethinking what they mean by “world literature.” These concepts of “world literature” and “global science” both have long and problematic histories. Ayesha, Marta, and I shared a wariness about the traps that past attempts to create disciplines with a global scope have fallen into, including their complicity with colonialism and neoliberalism. It was in the process of thinking about the challenges of producing global knowledge that we came to rest on these three modes that seem to have been uniquely persistent: the atlas, the encyclopedia, and the museum. As we were thinking about the ongoing histories of those ambitious modes of knowledge production, we realized that what we were really talking about was the phenomenon that goes by the name of “big data” today. And so bringing a historical perspective to the promises and challenges of big data became our central goal. From there, we tried to develop more specific questions that cut to the heart of the problems of big data—questions about privacy, inclusivity, bias, and so on.

One of the exciting things about developing the project has been the chance to work with five colleagues doing research in fields that are so far from mine, thinking together about the common problems, aspirations, and challenges that we all share when it comes to scaling up and thinking globally.  

SP: What do you see as things you will contribute to the Sawyer Seminar from your own research experience, or things you can bring to the project from your discipline?

DC: My efforts to learn more about the recent history of climate science have led me to join a collaboration between atmospheric scientists—physicists and chemists—and ecologists. Those might sound like disciplines that are very close to each other, and if you go back to the nineteenth century they do have common origins, but for much of the twentieth century they occupied very different disciplinary spaces. For most of the past seventy-five years or so, they haven’t really talked to each other. Their research strategies seem pretty incompatible. Ecologists are used to studying specific places, working at a local or regional scale, often studying systems that are very difficult to predict, sometimes very difficult even to quantify, often on the basis of specimen collections rather than instrumental measurements.

On the other hand, atmospheric scientists as a discipline pride themselves above all on their successes with weather forecasting. As they tell it, their field coalesced in the mid-twentieth century around computerized weather prediction. So to bring these two disciplines together, disciplines that work with different forms of data and different epistemic norms, has been complicated, but it’s absolutely necessary for addressing climate change, particularly questions of adaptation. I’ve been wondering how these cross-disciplinary dynamics between atmospheric science and ecology might be symptomatic of the broader challenges of trying to collaborate on large sets of data across disciplines. And I think as we try to produce global models of everything from the economy to epidemiology we are increasingly trying to bridge very different data sets and different epistemic norms. This is a problem I’m thinking about under the catchphrase of “data diversity,” a phrase I like because it also points to the very urgent problem we face today of algorithms that can hide all kinds of biases.

SP: Why do you think it is important to be talking about how we manage information at this particular moment? Is there a particular urgency you see based on where our world is now?

DC: I think the COVID-19 outbreak shows how much we rely on global data to survive in the world today, and the ways in which many of us don’t stop and think about where that data comes from, how it’s produced, what its contingencies are, and the ways in which the form that it’s given influences our responses. So we think of data as inherently objective, without interpretation, but in fact data always comes to us heavily mediated and in forms that we need to recognize as themselves interpretations. For instance, graphs of infection rates rarely represent the uncertainty in the data on the number of cases or deaths from the virus, which gives a false sense of complete knowledge. I think that with the current pandemic there’s a lot that lends itself to critical analysis: we need to pay attention to the aesthetics of data and its narratological qualities, the ways it’s made to tell stories.

SP: What are you most excited about for the future of this project? What kinds of conversations do you hope the Sawyer Seminar will engender?

DC: I’ve only been at Yale for two and a half years, but I’ve been struck by how well it supports cross-disciplinary exchange. I’m very excited to be part of this project here at Yale in particular, especially since one of our foremost goals is to better connect faculty to Yale’s collections: its museums, galleries, rare book repositories, and archives. So part of what I’m looking forward to is serendipity: to the chance to view an object from, say, the Peabody Museum of Natural History in a space dedicated to the arts or humanities, and seeing what kinds of new questions and new insights those juxtapositions will create. I’m also excited about the prospect of engaging our colleagues in data science in this project and hopefully laying the foundations for future conversations between data scientists and humanities scholars.

I should also mention my gratitude to Naveeda Khan, who, when she visited Yale in February, gave us a lot of really helpful input based on her experience organizing a Sawyer Seminar on a related theme at Johns Hopkins University. I think it’s wonderful that the Mellon Foundation is not only helping us build new connections within Yale, but also, by seeding Sawyer Seminars with related concerns across institutions, actually allowing us to make nationwide connections.