There’s an inherent flaw embedded in the essence of machine learning: your system will learn from data, putting it at risk of picking up on human biases that are reflected in that data.
Essentially bias is the phenomenon where the model predicts results that are systematically distorted due to mistaken assumptions. A biased model is a model that produces large losses or errors when we train our model on a training set and evaluate our model on a test set.
Learn more about AI Bias here.
