Resumes are fighting the good fight to stay relevant. But more and more, leaders who are embracing social change and diversity as they seek the best talent assert that this "important" piece of paper deserves the trash can. And according to Jake Hsu, CEO of software engineering service company Catalyte, the biggest reason to shred this old standard isn't logistics or poor efficiency--it's bias.

Evidence of a problem

Multiple studies back up Hsu's assertion. For example, in 2003, the National Bureau of Economic Research found that resumes with "white-sounding" names spurred 50 percent more callbacks than the ones with "black-sounding" names. And a 2016 study published in the Harvard Business Review revealed that elite employers strongly discriminate based on social class, preferring male applicants from higher-class backgrounds. This might stem, at least in part, from centuries-old, traditional patriarchial systems in which only white males were allowed the privilege of expensive education and, subsequently, were associated with intelligence and specific capabilities. It's the desire to "dance around class", as Hsu puts it, that has caused employers to hold on to resume use.

"Our fundamental belief is that employment should be based on aptitude, not pedigree (where you went to school, the family you were born into, even where you live geographically). Because most hiring today in the US is still resume focused (including other companies that use AI as part of their HR suite), we believe there are many Americans, especially in underserved communities, who are not realizing their full potential."

But how do we fight that pedigree concept in hiring?

Catalyte has one possible answer that leans on--what else?--artificial intelligence.

The idea of using artificial intelligence during the hiring process isn't new. In 2017, for instance, Unilever created a new AI-based methodology to scan and sort applicant data, getting rid of roughly half of all initial candidates via the technology alone. But rather than look at typical areas like background or personality fit, Catalyte uses its proprietary AI algorithms and predictive analytics, developed via thousands of trial-and-error machine learning iterations, to identify coding-related skills in candidates. Those candidates then are trained and placed with Fortune 500 companies. With their system, your current field or expertise doesn't hold the critical keys to you getting hired. Your potential to complete a specific task does. And importantly, it can overcome your own bias, too--you might not see yourself as a techie, for example, but the AI won't lie about you meeting specific criteria.

How Catalyte finds the perfect hire

Hsu explains the basic process:

"We collect background information in addition to resumes. A big part of the screening is having our candidates fill out their background information (we don't ask for race or sex or geographic) and this is where our team really gets a deep understanding of who our candidate is.

"During the two hour screening, Catalyte is not just asking the candidate questions, but we are collecting meta-data like keystrokes and how long it takes him or her to open browsers, and this allows us to collect stimuli. Our team really wants to focus beyond just the standard 'scoring' of their best - we really put a strong focus towards the candidate's interaction with the screening, how they respond to questions, and their approach to problem solving. Their cognitive agility and reaction to stress speaks volumes to us."

Putting real money behind the hiring change

Catalyte's approach has caught the eye of investors, including Lady Gaga's former manager and co-founder of VC firm Cross Culture Ventures, Troy Carter. In fact, in a February statement, Carter asserted that Catalyte "provides a real solution to tech's diversity problem" and has the chance to deliver better business outcomes. Catalyte also just completed a $27M Series A funding round and acquired software development and consulting service company Surge.

And Catalyte is expanding quickly. Just this week, the company announced that it is opening a new development center in Chicago. Hsu hopes to open a total of 20 such centers across the United States by 2020 to find more talented individuals who otherwise might be overlooked for tech jobs.

But the really exciting news is this

While Catalyte focuses on coding at the moment, Hsu says the concept could be expanded. New algorithms could focus on linguistics or math, for example. That means we soon could have an entirely new approach to hiring where employers can use AI-based screening to identify candidates with any skill or skill set that most benefits their industries and companies. As an example, Catalyte's founder, Michael Rosenbaum, created a separate company, Arena, to do what Catalyte does, geared specifically for the healthcare industry.

But Hsu offers one caution:

"The biggest challenge, regardless of industry, is that, for AI to be an effective tool in hiring, you need to know what success looks like in a position. For software development, that is easier to define than in some other professions. You have direct and objective data that shows the productivity and outcomes of an individual. In some other fields, say law or graphic design, defining success is more subjective. I suspect AI will eventually develop to the point where other industries adapt similar methods to find the best talent."

For individual well-being, economic stability and social equality, let's hope that Hsu's "eventually" translates to "really, really soon".