How Much Time Would You Spend on Deep Learning?

Bias can be a relevant point of data or a sensitive point of data that you don't want the algorithm to learn. If we had gender in there, and all of a sudden the model starts predicting that some bad condition is always happening more predominantly with men versus women, that's bias. The one that's more sensitive stuff like race, when that's either intentionally or unintentionally added to a model, that's bad. It's how we perpetuate discrimination with through the lens of opacity of our data. Our decisions as humans are flawed and our data is based on those biases.