Hagey Lecture looks at the dark side of Big Data
We live in the age of the algorithm. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as mathematician and author Cathy O’Neil reveals, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.”
Welcome to the dark side of Big Data.
About the speaker
Cathy O’Neil is the author of the blog mathbabe.org and the New York Times best-selling Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, which was a semifinalist for the National Book Award.
She earned a PhD in math from Harvard, was a postdoctoral fellow in the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She then switched over to the private sector,, working as a quantitative analyst for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. She left finance in 2011 and started working as a data scientist in the New York start-up scene, building models that predicted people’s purchases and clicks.
Cathy wrote Doing Data Science in 2013 and launched the Lede Program in Data Journalism at Columbia in 2014. She is a columnist for Bloomberg View.