In episode 50, our Season 1, 2018 finale of DataFramed, the DataCamp podcast, Hugo speaks with Cathy O’Neil, data scientist, investigative journalist, consultant, algorithmic auditor and author of the critically acclaimed book Weapons of Math Destruction. Cathy and Hugo discuss the ingredients that make up weapons of math destruction, which are algorithms and models that are important in society, secret and harmful, from models that decide whether you keep your job, a credit card or insurance to algorithms that decide how we’re policed, sentenced to prison or given parole? Cathy and Hugo discuss the current lack of fairness in artificial intelligence, how societal biases are perpetuated by algorithms and how both transparency and auditability of algorithms will be necessary for a fairer future. What does this mean in practice? Tune in to find out. As Cathy says, “Fairness is a statistical concept. It's a notion that we need to understand at an aggregate level.” And, moreover, “data science doesn't just predict the future. It causes the future.”LINKS FROM THE SHOW

DATAFRAMED SURVEY

DataFramed Survey (take it so that we can make an even better podcast for you)

DATAFRAMED GUEST SUGGESTIONS

DataFramed Guest Suggestions (who do you want to hear on Season 2?)

FROM THE INTERVIEW

Cathy on Twitter
Cathy's Blog Mathbabe
Weapons of Math Destruction: How big data increases inequality and threatens democracy by Cathy O'Neil
Cathy's Opinion Column, Bloomberg
Doing Data Science (By Cathy O'Neil and Rachel Schutt)
Cathy O'Neil & Hanna Gunn's "Ethical Matrix" paper coming soon.

FROM THE SEGMENTS

Data Science Best Practices (with Heather Nolis ~20:30)

Data Science Best Practices (with Ben Skrainka ~39:35)

Original music and sounds by The Sticks.

#50 Weapons of Math Destruction

DataFramed

#50 Weapons of Math Destruction