  Bias is known to be an impediment to fair decisions in many domains such as
human resources, the public sector, health care etc. Recently, hope has been
expressed that the use of machine learning methods for taking such decisions
would diminish or even resolve the problem. At the same time, machine learning
experts warn that machine learning models can be biased as well. In this
article, our goal is to explain the issue of bias in machine learning from a
technical perspective and to illustrate the impact that biased data can have on
a machine learning model. To reach such a goal, we develop interactive plots to
visualizing the bias learned from synthetic data.
