I've posted a few things around AI, so when I found this I thought it would help explain a bunch of questions I still had. And I wasn't wrong.
It would appear that saying "with great power comes great responsibility" (Apparently not from Spiderman 1962, but derives from France in 1793).
You need to be careful how you use the data you have, what you focus on before using it to make decisions, or worse building an algorithm to fundamentally change any process.
“If you always do what you’ve always done, you always get what you’ve always gotten.” – Source
At which point removing any type of bias from an algorithm, is actually very difficult, and requires deep subject knowledge and lots of trials and simulations.
In the case of Amazon’s recruiting tool, an “attribute” could be the candidate’s gender, education level, or years of experience. This is what people often call the “art” of deep learning: choosing which attributes to consider or ignore can significantly influence your model’s prediction accuracy. But while its impact on accuracy is easy to measure, its impact on the model’s bias is not.
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