AI And The Hiring Elephant
by Miki Saxon
Yesterday we looked at some terrible management advice; today we’ll check out the unstated, totally ignored elephant in the room when it comes to hiring.
When AI tells you the success of your new hire, before you hire them is a typical misleading media headline.
While the experts talk about the enormous amount of candidate data available online that goes way beyond education, skills, experience and even background checks, and AI’s ability to correlate and to some extent, interpret it, they agree that it still requires human involvement.
But comprehending someone’s motivations and soft skills – attentiveness, nimbleness or assertiveness — requires a level of interpretation that some recruiters don’t believe machines have just yet. (…)
That type of intuition is already being built into machines. In the hiring process, the data to analyze is flooding in and it will require powerful and intelligent machines to digest it all; companies are realizing they need to be more precise about their hiring needs in order to get answers from machines; and already we’re seeing some machines conduct simple tasks, such as administrative matching.
Once again the elephant is ignored.
All focus is on candidates, while the elephants are completely ignored.
What are the elephants?
The manager and the culture they create in their individual domain all the way down to a team leader.
That’s why the person who soars as a star working for X can easily burn out and crash after going to work for Y and vice versa.
The elephants aren’t new; they’ve always been around and even occasionally written about, but rarely credited with candidate success or failure.
Will/can AI change that?
Unlikely, because, as seen in hundreds of examples, self-analysis is rarely accurate and how someone wants to be managed is not necessarily predictive of how they will manage others.
So, as long as the elephants continue to roam and thrive, it remains unlikely that AI will actually be able to predict hiring success.
Image credit: David Blackwell
