When I started my Ph.D. program somebody warned me that being an interdisciplinary scholar is not a synonym for being mediocre at many things. Rather, choosing an interdisciplinary path means having to work just has hard as your disciplinary colleagues, but doing this equally well across multiple disciplines.

I suspect that comment doesn’t really do justice to the challenges faced by scholars within more established disciplines, but I can definitely attest to the fact that working across disciplines can be a challenge.

Having worked in academia for many years, I’d been prepared for this on a bureaucratic level. My program is affiliated with multiple departments and multiple colleges at Northeastern. No way is that going to go smoothly. Luckily, due to some amazing colleagues, I’ve hardly had do deal with the bureaucratic issues at all. In fact, I’ve been quite impressed to find that I experience the department as a well-integrated part of the university. No small feat!

But there remain scholarly challenges to being interdisciplinary.

This morning, I was reading through computer science literature on argument detection and sentiment analysis. This relatively young field has already developed an extensive literature, building off the techniques of machine learning to automatically process large bodies of text.

A number of articles included reflections how how people communicate. If someone says, “but…” that probably means they are about to present a counter argument. If someone says, “first of all…” they are probably about to present a detailed argument.

These sorts of observations are at the heart of sentiment analysis. Essentially, the computer assigns meaning to a statement by looking for patterns of key words and verbal indicators.

I was struck by how divorced these rules of speech patterns were from any social science or humanities literature. Computer scientists have been thinking about how to teach a computer to detect arguments and they’ve established their own entire literature attempting to do so. They’ve made a lot of great insights as they built the field, but – at least from the little I read today – there is something lacking from bring so siloed.

Philosophers have, in a manner of speaking, been doing “argument detection” for a lot longer than computer scientists. Surely, there is something we can learn from them.

And this is the real challenge of being interdisciplinary. As I dig into my field(s), I’m struck by the profound quantity of knowledge I am lacking. Each time I pick up a thread it leads deeper and deeper into a literature I am excited to learn – but the literatures I want to study are divergent.

I have so much to learn in the fields of math, physics, computer science, political science, sociology, philosophy, and probably a few other fields I’ve forgotten to name. Each of those topics is a rich field in it’s own right, but I have to find some way of bringing all those fields together. Not just conceptually but practically. I have to find time to learn all the things.

It’s a bit like standing in the middle of a forrest – wanting not just to find the nearest town, but to explore the whole thing.

Typical academia, I suppose, is like a depth first search – you choose your direction and you dig into it as deep as possible.

Being an interdisciplinary scholar, on the other hand, is more of a breadth first search – you have to gain a broad understanding before you can make any informed comments about the whole.


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