Biography
Prasanna Parasurama is an Assistant Professor of Information Systems and Operations Management at Emory University’s Goizueta Business School.
His research studies AI, labor markets, platform design, and human-AI collaboration.
Some of his recent work examines how AI and market design shape labor-market matching, failure modes of AI in Human-AI collaborative settings, and how AI can be designed to complement human expertise.
His work has been published in leading peer-reviewed outlets including Management Science and Administrative Science Quarterly.
Prior to joining Emory, he received his PhD in Information Systems from NYU Stern and worked in the industry as a data scientist.
Applying While Black: The Collateral Effects of Racial Differences in Work Histories
Administrative Science Quarterly
Prasanna Parasurama, Ming D. Leung, Sharon Koppman
May 27, 2026
2025
It is well known that hiring practices that treat job seekers differently by race contribute to racial disparities in employment. Yet, practices that treat job seekers equivalently may also contribute to racial disparities if there are pre-existing racial differences among the applicants. We focus on employers’ prominent practice of using job seekers’ work histories to make inferences about their suitability for jobs. Scholars and practitioners alike have long assumed that work histories are race neutral because they result from job seekers’ strategic choices about where to apply and what jobs to accept. However, Black job seekers face structural constraints—namely, anticipating and experiencing racial discrimination—that restrict the job search strategies and resulting jobs available to them.
It is well known that hiring practices that treat job seekers differently by race contribute to racial disparities in employment. Yet, practices that treat job seekers equivalently may also contribute to racial disparities if there are pre-existing racial differences among the applicants. We focus on employers’ prominent practice of using job seekers’ work histories to make inferences about their suitability for jobs. Scholars and practitioners alike have long assumed that work histories are race neutral because they result from job seekers’ strategic choices about where to apply and what jobs to accept. However, Black job seekers face structural constraints—namely, anticipating and experiencing racial discrimination—that restrict the job search strategies and resulting jobs available to them.
The Production and Consumption of Social Media
Management Science
Apostolos Filippas, John J. Horton, Elliot Lipnowski & Prasanna Parasurama
May 27, 2026
2025
We model social media as collections of users producing and consuming content. Users value consuming content but due to scarce attention they may not value all content from other users. Users also value receiving attention, creating the incentive to attract an audience by producing valuable content but also through attention bartering—users mutually becoming each others’ audience. Attention bartering shapes substantially the patterns of production and consumption on social media, explains key features of social media behavior and platform decision-making, and yields sharp predictions that are consistent with data we collect from #EconTwitter. We conduct Twitter and Instagram user surveys that yield additional direct evidence in support of attention bartering, and we discuss the implications of attention bartering for the design of social media platforms.
We model social media as collections of users producing and consuming content. Users value consuming content but due to scarce attention they may not value all content from other users. Users also value receiving attention, creating the incentive to attract an audience by producing valuable content but also through attention bartering—users mutually becoming each others’ audience. Attention bartering shapes substantially the patterns of production and consumption on social media, explains key features of social media behavior and platform decision-making, and yields sharp predictions that are consistent with data we collect from #EconTwitter. We conduct Twitter and Instagram user surveys that yield additional direct evidence in support of attention bartering, and we discuss the implications of attention bartering for the design of social media platforms.