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Catherine Tucker | Data Deserts, Algorithms, and Inequality

Catherine Tucker | Data Deserts, Algorithms and Inequality
February 27, 2023
Hybrid event
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Catherine Tucker joined us on Monday, February 27, 2023, to talk about “Data Deserts, Algorithms, and Inequality.”


Data brokers use black-box methods to profile and segment individuals for ad targeting, often with mixed success rates. We present evidence from four countries and five complementary field tests that differences in profiling accuracy and coverage for common demographic attributes mainly depend on who is being profiled. Consumers who are better off – for example, those with high incomes and a college education – have personal backgrounds that are profiled more accurately or ensure that there is any available profile information. In addition, occupational status (white-collar vs. blue-collar jobs), the ethnic background, gender, and household arrangements also affect the accuracy and likelihood of having a profile that is covered by data brokers.

Our analyses suggest that consumer-background profiling errors are driven by the scope of people’s digital footprint, which in turn reflects socio-economic status. Those who come from lower-income backgrounds have smaller digital footprints, leading to a `data desert’ for such individuals. In contrast, vendor-specific effects spanning different classification methods and algorithms appear to barely explain greater profiling accuracy. However, vendor-specific networks and partnerships do matter. They affect profiling outcomes indirectly due to differential access to individuals that vary in their background. We also show that audience pricing is sub-optimal and does not account for attribute- or consumer-related accuracy differences.

About Catherine Tucker

Catherine Tucker

Catherine Tucker is the Sloan Distinguished Professor of Management and a professor of marketing at MIT Sloan. She is the faculty director of the EMBA program. She has also been the chair of the MIT Sloan PhD Program.

Her research interests lie in how technology allows firms to use digital data and machine learning to improve performance, and in the challenges this poses for regulation. Tucker has particular expertise in online advertising, digital health, social media, and electronic privacy. Her research studies the interface between marketing, the economics of technology, and law. 

She has received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for an Emerging Female Marketing Scholar and Mentor, the Garfield Economic Impact Award for her work on electronic medical records, the Paul E. Green Award for contributions to the practice of Marketing Research, the William F. O’Dell Award for most significant, long-term contribution to Marketing, and the INFORMS Society for Marketing Science Long Term Impact Award for long-run impact on marketing. 

She is a co-founder of the MIT Cryptoeconomics Lab which studies the applications of blockchain. She has been a Visiting Fellow at All Souls College, Oxford. She has testified to Congress regarding her work on digital privacy and algorithms, and presented her research to the OECD, World Bank, IMF, and the ECJ. 

Tucker is senior editor at Marketing Science. She has been coeditor at Quantitative Marketing and Economics and associate editor at Management Science, Marketing Science, and the Journal of Marketing Research. She is the co-director of the program on Digital Economics and Artificial Intelligence at the National Bureau of Economic Research.

She teaches MIT Sloan’s course on Pricing and the EMBA course “Marketing Management for the Senior Executive.” She has received the Jamieson Prize for Excellence in Teaching as well as being voted “Teacher of the Year” at MIT Sloan.  

She holds a PhD in economics from Stanford University and a BA from the University of Oxford. 

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