Imagine if you had a strawman so full of straw, it was the most strawfilled man that ever existed.
From the article:
> “What is clear is that it’s going to be really difficult to mitigate these biases,” says Judy Gichoya, an interventional radiologist and informatician at Emory University who was not involved in the study. Instead, she advocates for smaller, but more diverse data sets that test these AI models to identify their flaws and correct them on a small scale first. Even so, “Humans have to be in the loop,” she says. “AI can’t be left on its own.”
What do you think smaller data sets would do to a model? It'll get rid of disparity sure