Title: Measuring bias in social network ad targeting and delivery.
The enormous financial success of online advertising platforms is partially due to the precise targeting and delivery features they offer. Recently, such platforms have been criticized for allowing advertisers to discriminate against users belonging to sensitive groups, i.e., to exclude users belonging to a certain race or gender from receiving their ads. In this talk, I discuss two threads of work that aim to understand the extent of discrimination in ads on online platforms
Bio
Alan Mislove is a Professor and Associate Dean and Director of Undergraduate Programs at the Khoury College of Computer Sciences at Northeastern University, which he joined in 2009. He received his B.A., M.S., and Ph.D. in computer science from Rice University in 2002, 2005, and 2009, respectively. Prof. Mislove’s research concerns distributed systems and networks, with a focus on using social networks to enhance the security, privacy, and efficiency of newly emerging systems. He work comprises over 50 peer-reviewed papers, has received over 12,500 citations, and has been supported by over $6M in grants from government agencies and industrial partners. He is a recipient of an NSF CAREER Award (2011), a Google Faculty Award (2012), a Facebook Secure the Internet grant (2018), the ACM SIGCOMM Test of Time Award (2017), the IETF Applied Networking Research Prize (2018, 2019), the USENIX Security Distinguished Paper Award (2017), the NDSS Distinguished Paper Award (2018), the IEEE Cybersecurity Award for Innovation (2017), a Facebook Secure the Internet Grant, and his work has been covered by the Wall Street Journal, the New York Times, and the CBS Evening News.
