Columbia Business School’s Bo Cowgill has pretty much everything we look for in a Best 40 Under 40 MBA Professor. A solid academic and professional background? Check. Robust award-winning research? Absolutely. Impact within the business school and university? Yes. Glowing nominations from current and former students? Yes, that, too.
“Bo Cowgill is the best professor I’ve had at CBS,” one nominator told us. “His course, People Analytics & Strategy, helped to evolve my own views on hiring, retention, and talent management. His former Google experience brought an analytical and corporate lens to the classroom. It was his class that inspired me to take a python class at the business school and implement my own hiring screen at work based on what I learned in class. Outside of the classroom, Professor Cowgill is the quintessential advisor and friend. When I wanted to do an independent study, following our class, on the effects of salary bans (as NYC has just implemented one), Professor Cowgill jumped at the opportunity and helped frame a curriculum around my interest and made himself available whenever I had a question. His influence on business practices and trends, public policy, and data has been pronounced on my understanding of the world.”
After earning his bachelor’s degree from Stanford, Cowgill went to a company called Google and worked for a guy named Hal Varian — Google’s Chief Economist. Varian was the founding dean of the University of California-Berkeley’s School of Information and also taught at the Haas School of Business. Eventually, Cowgill left Google to earn his Ph.D. from UC Berkeley.
Since joining Columbia Business School in 2016, Cowgill has launched the People Analytics and Strategy elective, which helped Cowgill win the Aspen Institute’s 2019 Ideas Worth Teaching Award and landed Cowgill’s course on the Quartz 10-Most Foward-Thinking Business Courses of 2019 Award. His research has been cited nearly 1,000 times, according to Google Scholar. And his research looking at artificial intelligence and algorithms in hiring has been featured in outlets like The New York Times and Forbes.
“Professor Cowgill was the most influential professor for me at Columbia,” another nominator said. “The whole class is always well-organized, from the beginning to the end, and each element of his lecture was constantly connected with each other, which reminds us of the important concepts that we should take away from the class. Student discussions were well-developed by his guidance, where everyone can raise their voice, sharing their own experience as an executive, which helped all of us learn from each other. As a former Google Engineer and Economist, he brought up new perspectives on the issue to think about during our discussion and this helped me understand the real-world application of People Analytics. I also learned a lot about the real-world issues not only from his research papers but also from the data assignment and guest speakers he invited.”
Current age: 39
At the current institution since what year? 2016
Education: BA, Stanford University, Ph.D., MS, UC Berkeley
List of MBA courses you currently teach:
- People Analytics and Strategy (Elective)
- Previously: Strategy Formulation (Core)
TELL US ABOUT YOUR LIFE AS A PROFESSOR
I knew I wanted to be a business school professor when… After college, I worked directly under Hal Varian, the Chief Economist at Google. Hal was a former professor at UC Berkeley Haas School of Business. He used his research expertise in market design to develop and refine the Google ads platform. Google as a whole was a great environment to see the value of research-like thinking in business. I stayed at Google for a few more years before leaving for my Ph.D.
What are you currently researching and what is the most significant discovery you’ve made from it?
My research is broadly about information and organizations, particularly information technology and labor markets. One strand of research is about algorithmic bias and fairness. One paper examines how corporations react to algorithmic fairness activism. I have a field experiment about operationalizing AI ethics. My paper about algorithmic social engineering examines the limitations of manipulating prediction algorithms to express policy preferences (a popular approach among some computer scientists).
I also have a field experiment on using AI in hiring decisions. Scientists have noted that human bias can be inherited by algorithms. However, human judgment is not only biased but also noisy and inconsistent. This fact is far less-studied but has important implications for algorithmic behavior. To learn optimal choices, algorithms need experiments. However, randomized trials are difficult to implement and are sometimes unethical or taboo. The noisiness of human judgment provides a coarse substitute. A noisy human is an unwitting experimentalist.
In a field test, I show that algorithms that harness human noisiness (even through simple approaches) substantially increase the productivity and the diversity of new hires. These results have implications for how training datasets are used in practice and regulated by governments. My article for the Journal of Economic Perspectives develops an economics-based perspective on algorithmic fairness.
A second strand of my research examines information and labor markets. I’m interested in how labor markets aggregate employers’ and candidates’ preferences. Measuring these effects requires methodological innovations. In one paper, we develop a new field experimental paradigm we call a “two-sided audit.” In another set of papers, we adapt methods from market design to study workforce segregation and bias in decision making.
These novel research tools offer new approaches for researchers studying a variety of pressing topics. My co-authors and I have used them to study labor market intermediaries, gender segregation at work, corporate overoptimism, the flow of information inside firms, workplace microgeography, deception in experiments, and salary history bans.
If I weren’t a business school professor… I would be an entrepreneur. Research and entrepreneurship have a lot in common. In both cases, there’s no “boss” giving you instructions. You have to generate ideas for a new product, gather the resources, move from idea to execution and ultimately produce and sell. Research is like entrepreneurship for ideas.
What do you think makes you stand out as a professor?
I teach content that is viscerally interesting, evocative and immediately relevant to today’s business world. However, I also connect these topics with deeper trends and more abstract concepts in social science.
These deeper trends and tensions have been lurking for decades (and will continue to be relevant). When the next crop of business challenges appear in our MBA’s lives, I want them to recognize familiar tensions resurfacing in new forms.
As an example, my People Analytics elective has sections about algorithmic bias and salary history bans. Our speakers have included Facebook’s head of People Analytics and leadership from Uber (essentially a people analytics company). Given that People Analytics draws some inspiration from sports, welcomed Rich Kleiman (Kevin Durant’s business partner and co-founder of Thirty Five Ventures) and RC Buford (5x NBA Champion, 2x NBA Executive of the Year and GM of the Spurs).
The students are free to ask the big, tough questions directly to our speakers (and to me). We use these contemporaneous topics as an entry point into bigger, evergreen ideas.
One word that describes my first time teaching: Excited!
Here’s what I wish someone would’ve told me about being a business school professor: Teaching your own elective is great! Developing an elective requires up-front costs, but also gives you a lot more flexibility and control once it’s done. It’s like the difference between entrepreneurship and regular employment.
Professor I most admire and why:
Professor John Morgan was my Ph.D. advisor. He is a brilliant economic theorist and a rare mentor possessing wisdom, wit and technical insight. John was previously featured in Poets&Quants for his innovative and energetic teaching style, which uses in-class games to teach economics.
What do you enjoy most about teaching business students?
Like all professors, I love seeing the moments when the light bulbs go off in our students’ heads. This doesn’t necessarily mean they agree with everything we’re talking about. However, it does mean they’ve figured out a new idea and how it works.
What is most challenging?
When you’re a newly-minted Ph.D., you’re accustomed to talking about business at two levels. Neither is good for an MBA class.
The first is the 5,000-foot view. This is how you’d summarize ideas for your friends or family with a casual interest in your job. It’s too shallow for MBAs, whose interests are non-casual (and who respect substance). The second is from deep within the weeds of academic or policy research. This view tends to be too tedious for an MBA classroom.
The challenge is to find a middle ground between these two extremes. MBA classrooms must engage students in vivid, memorable, and dramatic applications. However, the content must complement their existing interests and expertise while pushing their boundaries and theoretical foundations. This is a challenging but rewarding feat.
In one word, describe your favorite type of student: Outspoken. Even if the students and I disagree, everyone benefits when students speak honestly and spark dialogue.
In one word, describe your least favorite type of student: Credentalist!
When it comes to grading, I think students would describe me as… Fair
LIFE OUTSIDE THE CLASSROOM
What are your hobbies?
I have two little boys (4yo and 6yo) and I spend most of my spare time with them! I also play piano and guitar, and listen to lots of podcasts.
How will you spend your summer?
This year I’ll be teaching MBAs at Columbia. The summer is also an active time for conferences and research presentations in academia. I enjoy NBER Summer Institute; last summer my co-authors and I presented our work on salary history bans, and the summer before I presented work on experimental design for labor market intermediaries. I also frequently visit the AOM annual meetings. Our family sometimes travels in August, but we’ve so far stayed local (which is easier with small children).
Favorite place(s) to vacation:
I love the Sonoma Coast and Big Sur areas, which I came to know and love when I lived in California.
What is currently your favorite movie and/or show and what is it about the film or program that you enjoy so much?
I also enjoy biographies and/or memoirs of scientists and professors. For example: Misbehaving by Richard Thaler and The Undoing Project (about Kahneman and Tversky). Thinking Fast and Slow (by Kahneman himself) is also a bit of a memoir. And of course Zen and the Art of Motorcycle Maintenance!
I also like books about the creative process in the arts, in particular Impro (about improvisational theater, by Keith Johnstone) and Story (about screenwriting and plot, by Robert McKee). I’m an outsider to these fields.
Regarding fiction: I did not read Infinite Jest, either. However, I did enjoy Every Love Story is a Ghost Story. I read less fiction overall, alas. On the classics: I’ve always loved The Great Gatsby. This essay captures my reaction to Catcher in the Rye.
Lastly: Gödel, Escher, Bach is an inspiring book that defies comparison!
What is your favorite type of music or artist(s) and why?
I like all kinds of music. I’m excited about electronic music; it feels like it belongs more to our generation. However one non-electronic artist I love (and is underrated) is Punch Brothers. I had a great time watching Punch Brothers live with my colleague at Columbia Michael Mauskapf, who is himself a musician and musicologist.
Regarding art, I really like Paul Madonna‘s ink-on-paper cityscapes of San Francisco in his All Over Coffee series. The timespan of that collection is approximately the same as my residence in the Bay Area.
THOUGHTS AND REFLECTIONS
If I had my way, the business school of the future would have much more of this…
1) Technology and data sciences, 2) platform strategy, 3) entrepreneurship, 4) sustainability, non-market strategy and business-and-society overlap. If I had to add one other thing, it would be 5) leadership and “soft skills” (although this is already an area b-schools emphasize, to some degree).
In my opinion, companies and organizations today need to do a better job at…
Thinking creatively and independently, rather than following the herd. Also: Separating correlation from causation. Companies are investing more heavily in data science today, but most of their applications are still correlational. Causal relationships make insights more actionable.
I’m grateful for… My family’s health during COVID-19 and our heeding the warnings early.
Faculty, students, alumni, and/or administrators say:
“Congratulations to my colleague and friend Bo Cowgill for receiving this outstanding recognition. Bo designed and launched the course People Analytics and Strategy—about an area that has and is undergoing dramatic transformation through the incorporation of technology and innovative data analytics. The interplay of business and society is becoming ever more relevant to our students and alumni. Nowhere is this more obvious than how technology has shaped personnel management, organizational design, and hiring. Bo’s course is exemplary of our efforts to infuse more technology, data and analytics—and their applications in business settings and implications for society —across our curriculum. This ultimately will enhance the ability of our MBA students to lead and thrive in the digital future of business.” — Costis Maglaras, Dean of Columbia Business School
“Bo Cowgill is the best professor I’ve had at CBS. His course, People Analytics & Strategy, helped to evolve my own views on hiring, retention, and talent management. His former Google experience brought an analytical and corporate lens to the classroom. Outside of the classroom, Professor Cowgill is the quintessential advisor and friend. When I wanted to do an independent study following our class, on the effects of salary bans (as NYC has just implemented one), Prof. Cowgill jumped at the opportunity, framed a curriculum around my interest, and made himself available whenever I had questions. His influence on business practices and trends, public policy, and data has been pronounced on my understanding of the world.” — Isa Abney, Class of 2020
“What makes Professor Cowgill unique is his ability to create openness and build confidence in the decision-making ability of his students. He does this through in-class simulations, which encourage students to find solutions to real world people management problems. Professor Cowgill never tells his students what the answers are, rather he encourages students to think for themselves and defend a position, which is particularly important given that students will encounter these same problems at some point in their career. And who better to learn from than the economist who solved these problems at Google? Professor Cowgill is a former Google engineer. His research in people analytics, algorithmic bias and corporate prediction markets has been covered in the New York Times, Financial Times, and McKinsey Quarterly. He is an author or protagonist for several people analytics and algorithmic bias case studies and is truly an expert at the forefront of human capital management research. It’s because of Professor Cowgill that I plan on taking my career in a new direction, and I am grateful for him being available on weekdays and weekends to answer my questions.” — Rubin Srimal, 2020
“Professor Cowgill is in a category of one when it comes to bringing highly contemporaneous ethical topics into his classroom, case studies and research. His unique experiences as a practitioner of technology strategy helped considerably broaden my team’s perspective for our entrepreneurial venture. He stands out amongst his peers for his ability to provide theoretical context for many of the challenges faced by today’s companies at the forefront of the new digital economy. For instance, his insights into the driver hiring and retention practices for companies promoting the gig-economy – not only helped direct my independent study research, but also helped prepare me with palpable industry context for my interviews at Uber and AirBnB.” Shahryar Malik, 2018
“Professor Cowgill was the most influential professor for me at Columbia. The whole class is always well-organized, from the beginning to the end, and each element of his lecture was constantly connected with each other, which reminds us of the important concepts that we should take away from the class. Student discussions were well-developed by his guidance, where everyone can raise their voice, sharing their own experience as an executive, which helped all of us learn from each other. He brought up new perspectives on the issue to think about during our discussion and this helped me understand the real-world application of People Analytics. I also learned a lot about the real-world issues not only from his research papers but also from the data assignment and guest speakers he invited.” –Hyunyung Shin, 2021