Measuring discrimination that can be caused by data-driven algorithms, and finding ways to mitigate it has been one of the most important recent developments in computer science. In this talk, Muhammad Ali, computer scientist and Ph.D. student at Northeastern University, will provide a general introduction to the problems of algorithmic bias, and present a recent case study of Facebook ads. After launching several ads, his research measures how, in the absence of any ad targeting criteria specified by the advertiser, the platform’s powerful machine learning algorithms are able to skew the ad’s delivery along gender and race by themselves — including ads for legally protected categories such as employment and housing. The results of this research further the conversation that, in addition to the content creators, internet platforms share the responsibility for the content their users see.