Start Date: 8/25/2021 1:00 PM EDT
End Date: 8/25/2021 2:00 PM EDT
Venue Name: Zoom
Digital Analytics Association
Wednesday, August 25 | 1:00 PM - 2:00 PM ET
Firms employ algorithms because of their perceived profit-enhancing benefits, such as increased efficiencies from the computational power in conducting a variety of marketing activities. However, if the algorithms are biased, under certain conditions their use can backfire and lead to profit-reducing outcomes, such as lower demand for services. How can firms take into consideration how biased algorithms may directly reduce firm profits? What strategies can marketers employ today to reduce the detrimental effects of algorithmic bias?
In this session, Kalinda Ukanwa discusses her research on algorithmic bias and its impact on service demand. Her research offers insights into how managers can employ algorithms in ways that reduce detrimental effects of algorithmic bias on demand while maintaining or improving profits.
PhD, University of Maryland
MBA, M.S. and B.S, Stanford University
Kalinda Ukanwa is Assistant Professor of Marketing at the University of Southern California. A quantitative modeler, Professor Ukanwa researches how algorithmic bias, algorithmic decision-making, and consumer reputations impact firms. She is the winner of the 2018 Eli Jones Promising Young Scholar Award and a finalist for the 2018 INFORMS Service Science Best Student Paper Award, 2019 Howard/AMA Doctoral Dissertation Award, and the 2020 AMS Mary Kay Doctoral Dissertation Award. In a prior life, Professor Ukanwa was an industrial engineer, financial analyst, and finance executive at Walt Disney, Citigroup, Viacom, and Kaplan.