In 2017, artificial intelligence will play a big role in HR. Actually, it’s already here. Its not just a trend, however. It’s a complete evolution that will help HR face challenges facing leadership and talent management now. Like the cloud, it’s a technological sea-change when we really need it. But in HR we’re not sure what to do with it yet — so I’m here to help.
Here are four key ways AI will change HR for the better:
- It’s already waking us up. The world of work is marked by profound disruptions right now. We’ve gotten a little ho-hum about it all. But AI is a very big instance of a next big thing. It has huge, mostly positive implications for HR. HR Tech was buzzing with the signs of a big trend we’re actually excited about, even products trying to ride the wave, like same-old software being touted as “AI-enabled.” But you know something is poised to become the new normal when everyone is jumping to its Wiki definition. I highly recommend getting familiar with the concept of an intelligent machine — “a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.”
- It will help humanize the hiring process. No, that’s not a contradiction. AI has always been about human behaviors. The hiring process is still convoluted and getting to authentic face-to-face is being pushed farther down the line. If AI can be harnessed to helps screen and vet a thousand applicants, that’s good news. AI is bringing tools like word2vec, which will enable computing on natural language — the way we speak. With a properly built screening system screening resumes, hiring personnel can have human contact with candidates that much sooner.
- It will force us to deal with our data. Powerhouse analytics and the endless horizon of the cloud can’t run themselves. We still don’t know how to work it all — and I agree that AI isn’t the crutch we need to help us crunch all that data we have now. If we try to lean on AI as a way to handle that data, it’s not going to help us. For instance, a tool like word vectors requires great care is taken to input natural language descriptions that are varied, meaningful (as in not frivolous or buzzwords) and complete. The output is only as good as the input. And requiring smarter input takes us right back to dealing with all that data: What do we need? How can we use it? Because if we don’t, we won’t be ready to maximize this other amazing tool we now have.
- It’s another opportunity to fix unconscious bias. Despite our being well aware that bias is still a key problem in hiring, bias is still a key problem in hiring. A recent survey on hiring college graduates found that we’re still hiring people who remind us of ourselves. Thirty-seven percent of hiring managers who graduated from top schools said they prefer to only hire candidates from top schools. This is despite the fact that other criteria are ranked higher in importance in the actual workplace. For instance, “works well with others” ranks at 75%. “Coming from a top school” ranks at 35%. That’s not just bias. That’s foolish. AI can be used to take bias out of the screening equation when looking for candidates who the best qualified. It’s vital that we have a way to systematically ignore the factors that trigger human bias.
I see AI helping with a whole range of other HR issues, including the need to have more transparency. To look to AI as the great hope for creating transparency may sound counter-intuitive, but it’s not. Certain tactics that are simple targeting errors (like side-of-the-barn job ads that collect too many unqualified candidates) may not be any more that: just a mistake in judgment, or more likely, not enough time thinking through the task.
But a mistake like that can be damning to employer brand, turning off talent who don’t want to be considered treated like cattle. And the other side of this equation is that to a large extent, we expect a certain amount of data interference in our lives. We’re constantly barraged with cookies, with surveys, we’re always trying to teach our email apps how to separate spam. We dive into onboarding apps and personalize interfaces constantly. We already interact with machines. We have already assimilated them into our lives and our work cultures. Instead of arguing against AI as a robot invasion that’s going to erase the face of work, take a look in the mirror.
For more on HR tech trends, see Five HR Analytics Terms You Need To Know.