We're going to talk about five common types of algorithmic bias we should pay attention to: data that reflects existing biases, unbalanced classes in training data, data that doesn't capture the right value, data that is amplified by feedback loops, and malicious data.
In our final episode of Crash Course AI, we're going to look towards the future.
Jabril tries to make an AI to settle the question once and for all.
Search engines are just AI systems that try to help us find what we’re looking for.
