I am a sociologist working on machine learning fairness and ethical AI at Google. Before that, I was an Assistant Professor at the Institute of Communication, Culture, Information and Technology at the University of Toronto.
I received my PhD in sociology from the University of Wisconsin-Madison. My dissertation was the Machine-learning Protest Event Data System (MPEDS), a system which uses machine learning and natural language processing to create protest event data.
My research has focused on how new and social media has changed social movement mobilization and political participation. I rely on large-scale data collections and computational tools in my research, with an emphasis on automated textual analysis and machine learning. More recently, I've been interested in issues of fairness, accountability, and transparency in sociotechnical systems, and am interested in ways we can work to eliminate algorithmic bias in data science practice, as well as integrate those considerations into data science education.
I am also an activist, working on issues of queer and transgender inclusion in sports and higher education, and access to transgender health care.
In my spare time, I play women's flat track roller derby with Bay Area Derby.