Hands on Inquiry into Algorithmic Bias and Machine Learning Interpretability

Presented by Fatih Akici – Manager, Risk Analytics and Data Science at Populus Financial Group

As intelligent systems deepen their footprints in our daily lives, algorithmic bias becomes a more prominent problem in today’s world. The position of executives and data science leaders to this issue is generally reactive, in that, companies solely respond to the requirements coming from regulatory agencies. In this presentation, I am going to argue why the leaders should be proactive in identifying biases and how they will benefit from fixing them. I will demonstrate my point on an applied example.