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Artificial intelligence technology is officially on the scene when it comes to recruiting efforts. But to be frank, AI can be confusing (and potentially scary), and we get that.
Not all recruiting teams are on board with the AI train just yet, and many businesses may be wary of adopting technologies that can be difficult to understand. So we’re going to dive into what AI means for recruiting, a few of the main concerns that come with it, and how you can find the right AI solution for your hiring process.
First things first: How is AI Used in Recruiting?
Whether it is in the form of auto-screening candidates, assessing candidate qualifications, or even managing communication more effectively, artificial intelligence has numerous applications in the hiring process that can help recruiters to make their hiring decisions faster and with better data.
Without the help of AI-backed technology, recruiters can spend up to 40% of their time manually entering data into applicant tracking systems or sorting through resumes. This takes a toll on not only the productivity of your recruiting team (to say nothing of helping prevent burnout), but also lengthens the hiring process significantly, which can lead to disinterested and unhappy candidates. Besides, if you could reclaim 40% of your time every week, wouldn’t you?
What is Machine Learning? How is it Different?
You know how all thumbs are fingers, but not all fingers are thumbs? In a similar way, Machine Learning is a subset of artificial intelligence that focuses on using data and algorithms to effectively imitate the human learning process and gradually becomes more accurate over time. So, what does this mean for the recruiting process?
Machine Learning tools can be used to scan resumes, assess interview responses, and even rank candidates based on how well they may align with your company culture and values. While a recruiter can also effectively come to these conclusions, Machine Learning technology can support this process with more data, making the hiring process as a whole more efficient and faster for both recruiters and candidates.
Top 4 fears that recruiters have when they hear "automation."
Concerns with AI in Recruiting
We’ve said it before and we’ll say it again—AI is wonderful, but it also comes with some well-earned concerns.
One of the biggest benefits of AI in recruiting is the ability to mitigate biases and make hiring decisions solely based on a candidate’s qualifications. However, when it comes to video interviewing AI solutions specifically, one recent study has found that even while video interview platforms claim to mitigate bias, it is important to consider and explore “AI-based video interview technology’s potentially discriminatory effects,” especially as these types of interviews continue to gain popularity.
This is because many facial-analysis technologies can actually perpetuate biases rather than mitigate them, and they tend to have very high error rates with darker-skinned individuals — especially women of color. In fact, the error rate for facial recognition algorithms is up to 34% higher for darker-skinned females than it is for lighter-skinned males.
So How Do You Figure Out What’s Best for You?
Luckily, you can avoid many of these AI concerns by opting for phone interview software rather than video software. But there are still some crucial things to consider when you’re selecting an AI solution — unfortunately, not all AI solutions work the same. Recruiters should look for a solution that uses Machine Learning and Natural Language Processing AI technology, like Qualifi, because they serve as the backbone for a quicker and more efficient recruiting process.
Qualifi automatically transcribes interviews and uses these crucial AI technologies to scan the transcriptions and help recruiters filter interview responses by important keywords. This can be paramount to successful high-volume hiring as well as helpful for simply keeping the focus on only the most qualified candidates during the hiring process.
All in all, AI isn’t as mystifying as it may seem at first. It offers the potential to streamline your processes, while reducing the amount of time you spend on tasks that can now easily be automated. Remember that tech adoption is often a gradual process, so it’s okay to start by rolling out automated processes first, then slowly link more functionalities to AI. Remember to stay mindful of the potential biases that can be perpetuated with some AI algorithms, but be sure to jump on the AI train now, or risk being left in the dust.
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