Do You Know What Is Fair or Unbiased?

Bias is looks like just one technical term for the one person who is coding the algorithm, but bias creeps in at every point in your ML project life cycle. The way you collect the data, the way you label them can also be biased. So there are multiple checkpoints in this whole pipeline where things can go wrong. But it generally comes from top down and then slowly gravitates towards hybrid approach.