Databite No. 88: Cathy O’Neil

Weapons of Math Destruction

October 26, 2016 - 4:00 pm

Data & Society
36 West 20th Street, 11th Floor
New York, NY, 10011

Data & Society's speaker series – Databites – is geared toward engaging our network and the broader public on unresolved questions and timely topics of interest to the D&S community.

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This talk will also be streamed live.

Responses to Weapons of Math Destruction on Data & Society's Points.

Cathy O’Neil presents her new book Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy:

As algorithms increasingly mediate education, employment, consumer credit, and the criminal justice system, how do we measure their impact on our society?

Tracing her experiences as a mathematician and data scientist working in academia, finance, and advertising, Cathy O’Neil will walk us through what she has learned about the pervasive, opaque, and unaccountable mathematical models that regulate our lives, micromanage our economy, and shape our behavior. Cathy will examine how statistical models often pose as neutral mathematical tools, lending a veneer of objectivity to decisions that can severely harm people at critical life moments.

Cathy will also share her concerns around how these models are trained, optimized, and operated at scale in ways that she deems to be arbitrary and statistically unsound and can lead to pernicious feedback loops that reinforce and magnify inequality in our society, rather than rooting it out. She will also suggest solutions and possibilities for building mathematical models that could lead to greater fairness and less harm and suffering.

Cathy O’Neil is a data scientist and author of the blog She earned a Ph.D. in mathematics from Harvard and taught at Barnard College before moving to the private sector, where she worked for the hedge fund D. E. Shaw. She then worked as a data scientist at various start-ups, building models that predict people’s purchases and clicks. O’Neil started the Lede Program in Data Journalism at Columbia and is the author of Doing Data Science. She appears weekly on the Slate Money podcast.