Raw LLM Responses

@pepsiman4418First, thank you for watching the entire video. I appreciate you taking the time to do that. So let's say you have an HR manager that loves chess and thinks that chess is the best predictor of success. They also have absolutely nothing against women and would gladly hire a qualified women with absolutely zero bias of any kind. But, because they like chess, they decide to recruit exclusively from chess clubs at universities. They aren't saying "I don't want women", rather they are just saying "I want chess players," But, as it happens the overwhelming majority of chess players are men. So, when this HR manager, without any intent to harm women, exclusively hires from chess clubs, you wind up with an overwhelmingly male workforce. And that has nothing to do with women being unqualified...if the HR manager looked more broadly, they would find plenty of qualified women...but they choose not to. They choose to just look at chess players. So now we train an algorithm on this HR managers choices, which favor chess players, who are mostly male. The algorithm isn't told to exclude women, but what winds up happening is that the algorithm "learns" to prefer chess players. Then you feed the algorithm resumes from a whole host of sources (not just chess clubs), but the algorithm is already trained to prefer chess players, regardless of where the new resumes come from. So, it flags chess players to be interviewed. Those chess players, as we already said, are mostly male, thus the algorithm has perpetuated the (unintended) bias of the original HR manager. Now, I'm obviously exaggerating in that HR managers aren't just going to recruit from chess clubs, but what you DO find is that the default place to look for employees is wherever you came from yourself. And since most businesses have been male dominated for ages, the people making hiring decisions, disproportionately, are male. That means they tend to look in places where they feel comfortable looking (chess clubs or otherwise) and thus the outcome is biased, even if they don't intend the bias. I hope that helps explain things. Here's an article that discusses exactly how this played out when Amazon tried to implement AI to screen resumes: https://becominghuman.ai/amazons-sexist-ai-recruiting-tool-how-did-it-go-so-wrong-e3d14816d98e?gi=24b4e1830b4c