Racial Bias in Facial Recognition Software

This talk will cover the basics of facial recognition and the importance of having diverse datasets when building out a model. We’ll explore racial bias in datasets using real world examples and cover a use case for developing an OpenFace model for a celebrity look-a-like app.

About Stephanie Kim

Speaker Bio

Stephanie Kim is a Developer Evangelist at Algorithmia where she enjoys writing accessible documentation, tutorials, and scripts to help developers find fun and useful ways to incorporate machine learning into their smart applications.

She's the founder of Seattle PyLadies and is the co-organizer of Seattle Building Intelligent Applications Meetup. She enjoys machine learning projects, particularly ones where she gets to dive into unstructured text data to discover friction points in the UI or find out what users are thinking with natural language processing techniques. Her passions include machine learning, NLP, and writing helpful and fun articles that make machine learning accessible to anyone.

Speaker Experience: I've had the honor of speaking at three PyData's: https://www.youtube.com/watch?v=nFVjLSvK5po https://www.youtube.com/watch?v=aPy-1a1DUjo https://www.youtube.com/watch?v=thGCwESkXHU

I've also spoken at ACT-W, a women's tech conference: where I gave a talk that I turned into a blog post.