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Eliminating Bias

Jennifer Chayes

Technical Fellow and Managing Director at Microsoft Research
About this episode

Jennifer Chayes, spoke to us when she was a technical fellow and managing director at Microsoft Research. She believes data scientists should build algorithms with Fairness, Accountability, Transparency, and Ethics – or FATE. Jennifer now serves as Associate Provost and Dean at the University of California at Berkeley (UCB).


Attaining tenured status at a major university is often the culmination of an academic’s career; giving it up is unthinkable for most. But after 10 years at UCLA, Jennifer Chayes was offered a job at Microsoft. The offer, she says,“scared me to death,” but she took the job and became the managing director for Microsoft Research in New England, New York and Montreal.

“There are brass rings that come along, and they always come along at the most inopportune times, and they look really scary, but I believe that we should grab them when they come along,” Chayes says during a conversation with Stanford’s Margot Gerritsen, Stanford professor and host of the Women in Data Science podcast. Chayes is a big advocate of eliminating biases in search algorithms and believes that data scientists have “the opportunity to build algorithms with fairness, accountability, transparency and ethics, or FATE.” FATE, a group that formed at one of Chayes’ labs, works to address inequity in the field.

In one particular instance, the group discovered that certain searches yielded certain results. Searches looking for computer programmers, for example, typically returned results for people with male names. The change Chayes’ team implemented in the search algorithm removed that built-in bias. Removing bias from hiring is not only fair, it results in better outcomes, she says. “I think that you’re more likely to ask the right questions if you have been on the wrong side of outcomes. So you’re much more likely to see a lack of fairness or bias as a problem before it happens.” Chayes believes that the field of data science is changing and that the increase in underrepresented voices will be critical to the future of the field moving forward.

About the Host
Margot Gerritsen

Stanford Professor [Emerita] Margot Gerritsen is the Executive Director and co-founder of Women in Data Science Worldwide (WiDS) and born and raised in the Netherlands. Margot received her MSc in Applied Mathematics from Delft University of Technology before moving to the US in search of sunnier and hillier places. In. 1996 she completed her PhD in Scientific Computing & Computational Mathematics at Stanford University and moved further West to New Zealand where she spent 5 years at the University of Auckland as a lecturer in Engineering Science. In 2001, she returned to Stanford as faculty member in Energy Resources Engineering. Margot was the Director of the Institute for Computational & Mathematical Engineering (ICME) at Stanford from 2010-2018 and the Senior Associate Dean for Educational Affairs in Stanford’s School of Earth Sciences from 2015-2020. In 2022, Margot took Emerita status to devote herself to WiDS full time. Margot is a Fellow of the Society of Industrial & Applied Mathematics, and received honorary doctorates from Uppsala University, Sweden, and the Eindhoven University of Technology in the Netherlands. She now lives in Oregon with her husband Paul.

Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn.
Find out more about Margot on her Stanford Profile.