ISSR Scholars Mentor Seminar | "Does Representation Matter? Assessing how Representative Bureaucracy Shapes the Relationship Between Automation and Responsiveness to Public Service Requests" with Gregory Porumbescu
Talk Title: "Does Representation Matter? Assessing how Representative Bureaucracy Shapes the Relationship Between Automation and Responsiveness to Public Service Requests"
Automated technologies in public service are often portrayed as replacing human discretion and jobs. Advocates argue that substituting technology for government workers can streamline public services and enhance transparency, while critics warn that removing human judgment may undermine responsiveness—especially for clients needing personalized attention.
Despite these debates, empirical research on how workforce demographics shape automation’s adoption and outcomes remains limited. Noting this lack of evidence, we contend the job displacement narrative is overstated, suggesting instead that bureaucrats continue to play a vital role in service delivery—even in automated contexts. Building on representative bureaucracy theory, we propose that demographic congruence between public employees and the communities they serve influences the implementation and outcomes of automated service request systems.
To test this claim, we compiled a novel dataset of over a million service requests from five U.S. cities, merged with American Community Survey data and workforce demographic profiles obtained through FOI requests. Our findings show that representative bureaucracy significantly influences automation outcomes. In cities where workforces more closely reflect the public, government responses to underrepresented communities improve—especially in neighborhoods with historically lower engagement. We also pinpoint a key mechanism: frontline workers actively leverage automated systems to advocate for their own communities’ needs, a phenomenon amplified by workforce representation.
Contrary to the idea that algorithms simply eliminate human discretion, our research shows automation transforms discretion’s role and location in service delivery. In more representative workforces, frontline employees use automated systems to amplify representation of underserved communities. In less representative settings, these technologies often reinforce existing inequalities. We thus move beyond a narrow job replacement narrative to highlight how workforce diversity mediates technology’s impact on service equity, reframing automation as a redistribution of tasks rather than a mere elimination of discretion.
About the Speaker
Gregory A. Porumbescu (PhD, Seoul National University) is an associate professor in the Department of Public Administration and Policy at the University of Georgia’s School of Public and International Affairs (SPIA). His research centers on understanding the implications of technology for government transparency and accountability. Dr. Porumbescu’s work has been published in journals such as the Journal of Public Administration Research and Theory, Public Administration Review, Governance, and Social Science & Medicine. Prior to joining SPIA, Dr. Porumbescu served as an associate professor at Rutgers University–Newark. There, he was a co-founding principal investigator for the New Jersey State Policy Lab, an initiative dedicated to enhancing evidence based policy making in state governments. During his time at Rutgers, he was also appointed to serve on the AI, Equity, and Literacy Working Group, contributing to Governor Phil Murphy’s New Jersey AI task force. Dr. Porumbescu’s research has been supported by organizations such as the National Science Foundation, Korean Research Foundation, and the New Jersey Office of the Secretary of Higher Education.