In the paper, Ross, with co-authors David R. Anderson of Villanova University and Margrét V. Bjarnadóttir of the University of Maryland, explain how bias can be embedded in people analytics that uses AI, despite the AI itself being in principle free of bias. The authors also highlight best practices for human resource professionals and how to build a bias-aware analytical process that can prevent machine learning biases from creeping into HR practices.
“We show that it is not enough for algorithmic models to simply be race-blind or gender-blind; rather, these models need to affirmatively identify and correct for unwanted biases,” the authors write.
The white paper competition, sponsored by Google, included 28 submissions from around the globe that promoted data-driven, actionable insights from industry practitioners.
Ross came to the Warrington College of Business in 2015 after previously teaching at Columbia University. His research interests include the governance of firms, with a particular focus on gender issues in top management, and the formal foundations of strategy. Ross serves as an associate editor of Strategic Management Journal and on the editorial review boards of Academy of Management Review, Strategy Science and, prior to his associate editor position, Strategic Management Journal.
At Warrington, Ross teaches management strategy and entrepreneurship to MBA and specialized master’s students. He also advises doctoral students.
Ross earned his Ph.D. in economics from New York University, MBA from the University of Pennsylvania Wharton School and bachelor’s degree in economics and computer science from Binghamton University.