AI hiring…What are you ‘missing’?

Everyone who has worked in HR or as a ‘hiring manager’ for more than 10 years has experienced the tsunami of applications received when recruiting for an open position. AI, with their almost ‘magical’ algorithms, certainly takes away a lot of that burden. A push of a button and, ‘voila’, a small stack of virtually “guaranteed qualified applicants” are delivered. But what are you potentially missing when you turn over your initial selection process to AI?

Recruiting AI tools, when appropriately programmed, certainly reduce the volume of applications that aren’t truly relevant, saving labor time & cost. But when not appropriately programmed some very undesirable results can occur. For example:

• Amazon had been developing AI recruiting programs since 2014 with the goal of streamlining the search for talent. It’s AI program scanned applicants documents and gave a rating of 1 to 5 stars.
• But within a year Amazon discovered their program was not evaluating candidate in a gender-neutral way.
• Reuters has reported that Amazon has abandoned its online recruitment tool which used algorithms as it was sexist.
• The Department of Computer Science at University College London looked into how algorithms can ensure that they don’t inadvertently fall into gender bias, or impact other output results.
• A major drawback to using hiring algorithms is that when done incorrectly, they can be detrimental to an organization’s hiring practices, diversity and inclusion efforts and employer brand.

To the “diversity” & “inclusion” points. Companies often benefit by bringing in candidates with the requisite experience, say business development, from other companies. Why? They bring a fresh set of eyes to your company, its products, and services and how it’s approaching their target market. The ability to both replicate and innovate is critical to a company’s survival & growth.

But if the AI hiring tool you use isn’t programmed appropriately, it could be excluding dozens of potentially qualified candidates.

EG: you’re looking for a business development director for your manufacturing measurement devices.

• An applicant has 15 years as a manufacturing manager specifying and using devices like yours. And in their role at that company this individual worked closely with their BD director & collaborated on all these sales with their clients.
• This individual has clear technical knowledge of & experience with the equipment you want to sell. Plus, they have experience in the BD role.
• But because your AI ‘tool’ didn’t spot the phrase, “Business Development Director” when scanning the ‘titles’ on the CV, this potentially qualified candidate was never presented to you.

The ‘holy grail’ would be a system where AI can incorporate both “fit” and “difference” into its pre-evaluation. Unfortunately, AI is still in early stages of development in virtually all applications and this just isn’t currently possible.
So what’s still needed? Human review & judgment, just like in the ‘old days’ of only 10 years ago.

As a hiring manager myself I have always looked carefully at the indicators or ‘traits’ of the applicants to the positions I was filling.
I applied the human element by identifying the underlying skill set the candidates had developed & used in their prior positions. I did not solely look at their experience in the specific area I was hiring for.
I can personally attest that the vast majority of these individuals were some of the best performers I ever had join our team. Example: I hired a mechanical engineer who had no experience in smelter operations. He had an ME degree from a major university but ZERO experience in the field I was hiring for. He came from the Norfolk navy yards, rebuilding nuclear subs. But, he was smart, responsible, straightforward and reliable. He was one of the best hires I ever made. But if I’d relied solely on AI, his application would never have made it to my desk.
HPISolutions has the most modern ‘data analytics’ tools which can help your company identify the indicators and strengths of your candidates. Coupled with whatever AI ‘tools’ you’ve chosen to use, the combination could be a powerful approach for your company.
Your company should always ask, “why not?”
You can reach JP Rosso, the author of this article, to learn more about how HPISolutions can help you ask the questions that must be asked at jprosso@hpisolutions.com.