As I was nearing the third case study of Virginia Eubanks's Automating Inequality, I tweeted: "Studying class and income inequality has given me power where I have previously felt powerless. Reading Automating Inequality takes this feeling to new heights." Prior to reading this book, I knew that I wanted to leverage data analytics for social good, but I didn't know what that looked like. Eubanks not only shined a spotlight on the disturbing algorithms that drive inequality. She created a clear call to action for data nerds like me with a desire to do good in the world to dismantle these algorithms of oppression. I was must struck by the final case study focusing on child protection services and poverty. I don't have the book in front of me, but there was a line that child abuse and poverty look so much alike, and I was immediately reminded of my own experience as a child facing near starvation while my mother's abusive ex husband tried to frame the situation as abuse to take my brother and myself away from my mom. If North Carolina has employed those same models, would I have been able to stay with my mom? At the conclusion of this book, and in tandem with a Reply All podcast about l33t hackers, I felt compelled to overhaul my own data practices to build privacy. I don't know what someone like me can do to dismantle these oppressive systems, but I'm going to find out