You’re Probably Automating Your Recruitment Wrong. Here’s How to Fix That
When automation first entered the human resources space, many otherwise well-meaning HR departments embraced it with bit too much enthusiasm. You’ve doubtless heard some stories from that dark time. The earliest days of recruitment automation, when no one really understood what the technology was or how it worked.
Hiring software that eliminated otherwise qualified candidates based on a few meaningless keywords. Questionnaires which arbitrarily and impersonally sorted applicants into narrow boxes. Poorly-coded algorithms which, rather than displaying impartiality, were every bit as biased as the hiring managers who deployed them.
A lot has changed over the past several decades.
Machine learning is now more advanced than ever, capable of optimizing every phase of the recruitment process, from awareness through to onboarding. Some particularly advanced algorithms are even capable of examining a business’s talent pool in order to predict future hiring needs. Unfortunately, even with these considerable advancements, many recruiters still fall into the same trap as 20 years ago.
Namely, they rely too much on automation and too little on their own judgment and instincts.
The core problem, I think, is that they don’t fully grasp what AI is capable of. Yes, it’s incredibly powerful and beneficial. Yes, when applied properly, it’s capable of drawing out incredible insights that might otherwise have been overlooked.
At the same time, it’s very easy to misapply and overuse AI. An algorithm, after all, is only as good as the data-sets it is fed. As such, without analytics expertise and human intelligence to serve as a foundation for its algorithms, AI-driven recruiting software may cause more harm than good.
AI: Myths vs. Reality
Popular culture and the media are rife with examples of hyper-advanced AI.
Cyborgs and androids capable of displaying the full range of human emotion. Computers taking away human jobs, performing our duties better than we ever could. Supercomputers which, given the chance, would overthrow humanity in an instant.
The thing that any data scientist will tell you about the above examples is that AI as we currently know it simply doesn’t work that way. Machine learning is not currently advanced enough to exist totally independently of human guidance. It may never be.
Even the most advanced algorithms of today are incapable of experiencing the full range of human emotion. Even the most human-like AI is incapable of truly conceptualizing the unknown, creating things from sheer imagination or acting on instinct. And even the most advanced recruiting software is not a replacement for flesh-and-blood professionals.
“AI will create new opportunities for us to use our uniquely-human gifts like empathy, creativity, and affinity for discovery,” writes Steven ZoBel, Chief Product and Technology Officer for work management platform Workfront. “AI cannot be human…it is here to liberate us from routine jobs, and it is here to remind us what it is that makes us human.”
The Role of AI in Recruitment
In other words, AI is meant to augment your recruitment process, not overtake it entirely. Automation exists to make your job easier, streamlining the more routine aspects of your job and freeing you up to focus more on evaluating and selecting the best candidate possible for each position. As such, when you deploy it, there are several factors I would advise you to consider.
First, ask yourself why you need it. What part of the recruitment process are you looking to streamline and automate? Are you trying to make it easier to sift through CVs, or do you want a more comprehensive system for managing and connecting with approved applicants?
You must deploy automation with a goal in mind.
Second, lean on an expert to help you with your implementation. Machine learning is a surprisingly complex field, and while there are certainly cloud platforms that are easy to understand and deploy, there’s always something to gain by acknowledging your own knowledge and skill gap. Seek a third-party analyst, or attempt to train someone within your own organization.
Finally, understand that AI is not like traditional software. Deploying it is an ongoing effort. You will constantly revisit, tweak, and re-evaluate your algorithms and your overall platform, further refining your recruitment process over time.
By understanding that automation is not a panacea but simply another component of your toolkit, you’ll enhance and improve your recruitment in ways you never imagined possible.