Abstract: 

The concept of "biased data" is often too generic to be useful. Through a series of cases studies, we will explore what algorithmic bias is, different types (with different causes), and debunk some common misconceptions. We will cover why algorithmic bias is a problem worth addressing and some steps towards solutions.

Bio: 

Rachel Thomas is director of the USF Center for Applied Data Ethics and co-founder of fast.ai, which has been featured in The Economist, MIT Tech Review, and Forbes. She was selected by Forbes as one of 20 Incredible Women in AI, earned her math PhD at Duke, and was an early engineer at Uber. Rachel is a popular writer and keynote speaker.