2018: The Year Automation Takes Over Recruiting
By Adam Godson, Vice President of Global Technology Solutions
Much has been said the last few years surrounding how artificial intelligence is the wave of the future in recruiting. Lest you think it was all starting to sound like empty talk, 2018 looks to be the year when we will finally see real results -- successes, failures and lessons learned. This is the moment we will pinpoint when we look back to discover when the world changed.
What Will Change Look Like?
In this post-ATS era, technology companies have still mainly focused on a recruiter-centric model -- designing products aimed at giving the recruiter more time, and expanding their expertise and capabilities. The new model will be inside out, with machines acting as the "big brain" that can make the best decisions, while recruiters will use human interaction to fill the gaps of what machines cannot provide.
We have seen these models emerge in hourly hiring, specifically around retail and seasonal positions. This makes sense given how straightforward hiring for these jobs tends to be, and we expect many major retailers, restaurants and other employers of hourly talent will soon switch to fully automated recruiting. I feel safe saying this because we have seen the change in our business already, using a combination of technology and services to help companies get there faster. Cielo is already immersed in the automation of recruitment.
Fully automated recruiting involves using software -- in the form of chatbots, mobile applications, web applications, video or voice technology -- to do the work once done by people. Programmatic advertising replaces your ad agency or manual posting, scoring systems supplant the review of resumes and job applications, recorded video or voice calls and assessments take the place of prescreening interviews, and automated scheduling and onboarding replaces coordinators.
That might sound scary from a people perspective, but all these interconnected systems must still include human supervision. While the machine-learning algorithms fine-tune the matching that takes place in the system to drive toward superior results, human supervision is required to ensure those results continue to best serve the organization.
A Different Kind of Trust
Automated hiring models ultimately depend on the concept of computational trust. Even if you have not have heard that term, you use computational trust every day. When you're shopping for a new sweater in a store, you use observational trust. You feel the sweater's material for quality. You look around the store to see if it seems reputable. You try it on to see how it matches you. But when you are shopping online, you use computational trust. You look at the reviews to see how others rated the sweater. You look at sizing charts to see how it will fit. Seriously, when is the last time you ordered something that got terrible reviews?
The same concept applies to Uber or Airbnb. Your parents taught you never to get into a car with a stranger, but with a trust system in place you happily summon a stranger with your phone and get into their car (or, in the case of Airbnb, sleep at their house!). With automated hiring systems, the same concept applies -- managers will grow to trust the system to know that a 9.3 is likely a better candidate than a 5.7. And if it's not, people will feed the machine-learning algorithms so they can adjust.
Beyond Hourly Hiring
As these hourly models improve, the technology to advance them into more complex parts of the business will improve as well. For example, many hourly workers can be matched fairly well based on skills, shift, commuting distance and a few basic qualifying questions. But in our high-volume RPO model, we also are matching based on DiSC assessments, EQ assessments and voice or video analysis. With the continuous progress made by those technologies and machine-learning progress, someday we will be able to match a CFO as accurately as we can a cashier.
We are definitely on the precipice of a sea change in the way recruiting is done. Human judgment will give way to artificial intelligence in many processes, which is great from a business efficiency standpoint, but candidate experience still is going to play a huge part in hiring great people. That means this new automation still has to leave room for making those human connections, because technology is only as valuable as the human experience it provides.