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WATCH - An Experiment in Hiring Discrimination via Online Social Networks

Alessandro Acquisti - Carnegie Mellon University

November 25, 2013 12:00 PM  to 
November 25, 2013 1:00 PM
NSF Room 110

Alessandro Acquisti
Carnegie Mellon University

Abstract

Anecdotal evidence and self-report surveys suggest that U.S. firms are using Web 2.0 and social networking sites to seek information about prospective hires. However, little is known about how the information they find online actually influences their hiring decisions. We present two controlled experiments of the impact that information posted on a popular social networking site by job applicants can have on employers' hiring behavior. In two studies (a survey experiment and a field experiment) we measure the ratio of callbacks that different job applicants receive as function of their personal traits. The experiments (a survey experiment and a field experiment) focus on sensitive traits that are either unlawful or risky for U.S. employers to enquire about during interviews, but which can be inferred from applicants' online presences. Both the results from the survey experiments and those from the field experiment provide evidence of potential hiring discrimination via social networking sites.

Speaker

Alessandro Acquisti is an associate professor at the Heinz College, Carnegie Mellon University (CMU) and the co-director of CMU Center for Behavioral and Decision Research. He investigates the economics of privacy. His studies have spearheaded the application of behavioral economics to the analysis of privacy and information security decision making, and the analysis of privacy and disclosure behavior in online social networks. Alessandro has been the recipient of the PET Award for Outstanding Research in Privacy Enhancing Technologies, the IBM Best Academic Privacy Faculty Award, multiple Best Paper awards, and the Heinz College School of Information's Teaching Excellence Award. He has testified before the U.S. Senate and House committees on issues related to privacy policy and consumer behavior. Alessandro's findings have been featured in national and international media outlets, including the Economist, the New York Times, the Wall Street Journal, the Washington Post, the Financial Times, Wired.com, NPR, and CNN. His 2009 study on the predictability of Social Security numbers was featured in the "Year in Ideas" issue of the NYT. Alessandro holds a PhD from UC Berkeley, and Master degrees from UC Berkeley, the London School of Economics, and Trinity College Dublin. He has held visiting positions at the Universities of Rome, Paris, and Freiburg (visiting professor); Harvard University (visiting scholar); University of Chicago (visiting fellow); Microsoft Research (visiting researcher); and Google (visiting scientist). He has been a member of the National Academies' Committee on public response to alerts and warnings using social media.

To Join the Webinar:

The Webinar will be held from 12:00-1:00pm EDT on November 25, 2013 in Room 110.

To attend virtually, please register at: http://www.tvworldwide.com/events/nsf/130926/

This event is part of Webinars/Webcasts.

Meeting Type
Webcast

Contacts
Keith Marzullo, (703) 292-8950, kmarzull@nsf.gov

NSF Related Organizations
Directorate for Computer & Information Science & Engineering

Public Attachments
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