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We humans use AI in hiring to save hiring managers from many conflicts. That is why it was integrated into systems from many companies. Automation is known to make lives easier. That was the main reason individuals started depending on it for many tasks.
One of them is the tiring hiring process. Going through endless CVs and wanting to give every single one of them a fair chance of your time, judgement, and assessment. That is why people opted for AI automation options to hire employees. It was supposed to do the hard work for them and filter CVs based on certain given requirements.
However, at its core, AI is considered a mirror. One that reflects what it’s shown simply and most straightforwardly. So, if you train a system using decades of hiring data that favored men in tech roles and women in support roles, it won’t be so hard to guess what AI will learn, will it now? Yes, AI will unfortunately support the patriarchy.
The fact that men are better developers or doctors while women get to be the nurses or secretaries. And the result is us being in 2025 with a hiring process that makes us stuck in 1950. Disastrous? I agree. Want to solve it? Let’s find out how.
Amazon’s Lesson in Gender Bias
Back in 2018, Amazon proudly tested an AI-powered recruitment tool. This is a tool that was meant to redefine and smoothen up the hiring process. Instead, it quickly turned into an expensive reality check. One that had us raising our eyebrows. The algorithm started downgrading resumes that even hinted at femininity.
If we take a moment to ask why or see the reason behind it, we’ll find that it is because the machine had studied past data. One that came from a heavily male-dominated industry. Additionally, because it concluded that men were the “safer” or “smarter” hire. Amazon pulled the plug, but not before learning that automation without awareness can be a very costly experiment.
The Ups and Downs of AI in Hiring
Let’s give AI its due credit. We all know that it’s not a villain. There are still some benefits of course to it and to letting machines handle resumes:
- Speed: AI can review applications faster than you for sure.
- Consistency: No mood swings, no Sunday blues.
- Data-driven: Makes decisions based on information, not intuition.
- Scalability: Perfect for mass recruitment drives.
But here’s the twist: AI doesn’t know what’s right; it only knows what humans repeat. When past data is biased, the “smart” system becomes a not-so-smart machine. It becomes biased as well. And as a result, you’ll find yourself losing a lot of potential candidates.
The Machine’s Mirror
Coming from a female writer, it is safe to say that AI doesn’t hate women. It just doesn’t know any better. It takes inspiration from human history. And unfortunately, that history hasn’t been all that equal or fair in many aspects. This means that the problem doesn’t lie in bad coding. It lies in old misconceptions, sexism, and biased thoughts or past facts.
So how do we solve this? Diverse data through the eyes of diverse developers who keep on a constant human oversight in regard to the machines would do wonders that would save you from a lot of problems. Because until we teach AI empathy or at least context, it will keep reinforcing what we should be outgrowing. After all, how “intelligent” can AI really be if it simply cannot tell fairness from familiarity?
