How can an algorithms be biased?

Can algorithms really be biased?

In this talk, we will walk through the steps of how to build an algorithm to predict property prices from a dataset of property listings, focusing predominantly on finding the right features to include in building the model. Then, we will understand where in the feature engineering process we can start introducing bias into our algorithms, and what are the ramifications of this if the model were to be deployed and used in the real world. After understanding the basics of how bias can be introduced to a model, I’ll walk through a few real-world examples that highlight different algorithms and scenarios when algorithms led to biased (and at times racist) outcomes.