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Arvind Karunakaran joins MS&E as Assistant Professor

Prof. Karunakaran’s research examines authority and accountability at work in the context of technological change.
Professor Arvind Karunakaran

MS&E welcomes Arvind Karunakaran to our faculty!

Prof. Karunakaran received his PhD from the MIT Sloan School of Management. Most recently, he was an Assistant Professor of Strategy and Organization for the Desautels Faculty of Management at McGill University.

We caught up with Prof. Karunakaran to ask about his current work and why he chose MS&E. Read the brief Q&A below.

Can you describe your recent work and the impact you hope it makes, both in your field and in society?

I focus on the sociology of work and professions, which essentially means how different professional groups inside a workplace operate and the kind of conflicts that emerge between them, and especially looking at important social consequences of such conflicts. Specifically, I look at cases where newer professional groups have some oversight over more established professions—how they operate, what kind of challenges they face, and how successful they are. 

One example is when algorithmic auditors—a relatively new professional group—have oversight over software developers or computer scientists who create and deploy machine learning (ML) models and algorithms. Another is sustainability and ESG professionals in large companies. I look at how they manage sustainability initiatives, what kind of pushback they get, and how they implement—or fail to implement—their initiatives inside the company.

A specific project I’m working on studies the use of algorithms and technology in the hiring process. With the digitalization of the past 20 years or so, hiring is more democratized; many people can apply for a given job quite easily. But as a result, there are tons of applications for every job opening, and companies struggle to parse through the materials. To deal with this volume, many companies use some form of software—from a basic keyword-based filtering system to using machine learning—to screen resumes.

As you might anticipate, there can be issues in this process, especially because there is a whole cottage industry of consulting firms who train applicants to essentially game the algorithms. There's a constant back-and-forth between consultants and the companies, and in that process, they can make mistakes. And in some cases, there can even be legal implications for the company.

To combat these mistakes, the company I’m studying instituted a new group with backgrounds in computer science, law, and auditing. The group’s job is to interact with the mathematicians and computer scientists who develop the hiring algorithms and perform extensive testing every time a change is made. But there is a big tug-of-war, or jurisdictional conflict, going on between the two groups.

Practically, this work has a ton of implications, because a lot of companies are adopting these tools to make their hiring process easier. We don't yet know what kind of consequences this mass adoption will create, and how we can address them.

What does being a part of MS&E mean, or what makes it the right place for you?

I have a background in engineering; my undergraduate major was in Computer Science, and I have my master’s in Information Science. But more than that, the topics I study have precedence in MS&E, where there are people with social and behavioral science backgrounds as well as backgrounds in algorithms and CS. That mix of expertise keeps you on your toes, and you always want to learn new things.

I'd call it grounded interdisciplinarity, or a T model, because you have depth in one area, but also enough breadth of expertise to talk across other subgroups in the department. I think that’s important, in contrast to when interdisciplinarity means that you're not an expert in any one area. It makes MS&E a unique place, especially for the kinds of topics that I am interested in.