Skip to main content

It’s become a bit of a cliché, though the sentiment remains true: this past year has changed so much. Some for the better, and some for the worse.  

We’ve seen countless people lose their jobs, and while we’re slowly but surely recovering workers and hiring more and more as companies begin to expand again, we’re now doing so under new obligations that maybe could have but can no longer be ignored.  

For one, finding resilient workers is a must. Those who can withstand the pressures of drastic and sudden change, and who can adapt to their surroundings. Even further, hiring equitably is no longer a bonus, but rather a requirement.  

To change the workforce and tackle the systematic problem of inequity in workplaces, we must start by changing the ways in which we filter and screen and pre-screen job applicants—that is, doing so fairly and without bias or prejudice.  

According to a 2016 study by the Recruiter & Employer Sentiment Survey MRI Network, 56% of recruiters were unable to make good hiring decisions because of lengthy procedures. 

That’s time, money, and effort down the drain because of inefficient systems and practices.  

If you’re anything like me, you’ll constantly be on the lookout for new techniques and technology that can allow you to hire better.

Rest assured, this isn’t my first rodeo, and I’ve seen and tried many different filtration and screening and prescreening methods before landing on my own technology, so I can save you from doing the legwork yourself. 

Here are some of the best (and worst) tools and uses of technology available in HR.

Blockchain

Since its creation, blockchain has been adopted increasingly by many unique fields of work because of its flexibility and reliability.  

Known for its use in cryptocurrencies, the decentralized ledger is the perfect way to ensure infallible information records and secure data sharing methods.  

It has only been adopted relatively recently by the HR industry to recruit and view candidate credentials in a secure, reliable way, but of course, many of these systems are not comprehensive by any means.  

Particularly for those in the gig industry, blockchain allows workers to verify their credentials necessary to perform in a task or position by offering the employer or customer to view reliable and authenticated records from the worker’s background checker in real-time.  

Let’s say you want to hire an independent plumber who works outside of an established company, and want to see their qualifications to do major work in your home.

The plumber can share with you their licenses and certifications that have been authenticated by official credential issuers through blockchain, and cannot alter or falsify their information once verified.  

But this, ultimately, is where most uses of blockchain stop, in terms of its uses in HR. This means that while your background check can be performed reliably and faster than the traditional background check, your filtration process and candidate filtration for soft skills is not addressed whatsoever.  

Back to the drawing board it is! 

Artificial intelligence

Artificial intelligence (AI) has been commercially used to perform tasks over its years of evolution including medical diagnoses, robot control, remote sensing, and even problem solving in games (see: the computer who beats you every time at chess).  

It was only a matter of time, then, for AI to be integrated into a hiring and filtration system for recruiters and employers to be able to automate their lengthy and arduous processes.  

And while it has made filtering easier and speedier, especially with large numbers of applicants, AI has a history of being misused and can be accidentally—or intentionally—discriminatory when used to filter for job applications.  

Take for example, this innovative yet problematic use of AI that was designed to analyze a job applicant’s mannerisms, voice, and facial expressions in interviews. 

Of course, while the designers had intended to only highlight those who carried themselves well and presented themselves with the same confidence all of us are looking for in a candidate, their technology decidedly excluded those with disabilities and non-native speakers.  

But AI isn’t just used in novelty filtration tools.  

Many ATS (applicant tracking systems) also use AI to filter for criteria necessary for a job position, and this sounds in theory to be a great way to ensure the candidates that are moved to the next round are all up to the standards your position entails, but as we all know, keywords can be taken advantage of, and information can easily be falsified.  

On the other hand, you also have truthful candidates whose work is highlighted honestly on their applications, but the ATS doesn’t pick up on the keywords needed to pass them onto the next round because of a font discrepancy or the applicant’s CV is designed in a way that the ATS isn’t able to read. 

Not only are ATS unreliable for the above reason, they can also be discriminatory, as we’ve seen with Amazon’s experimental filtering process that degraded all female applicants’ information and read their credentials as lesser than their male counterparts’.  

And yes, they have discovered the process’s flaws since then and have removed the system from their hiring and screening process, but this technology has already cost them the many of potentially great employees who were overlooked and dismissed due to a systematic problem.  

In fact, according to a CareerArc/Future Workplace survey, 62 percent of companies who use ATS admit that “some qualified candidates are likely being automatically filtered out of the vetting process by mistake.” 

Though the problem lies in not AI itself but the ways in which it functions in a filtering system, why would you risk something like this happening to your organization, too, when you have so much to lose in adopting and learning an entirely new way of hiring that may or may not work. 

Our solution is, while admittedly biased, the best to avoid these missteps and take advantage of the great benefits technology can offer us in the HR industry today.

Personality assessments and aptitude tests 

As mentioned previously with blockchain, although some filtration and hiring processes can be effective in the hiring stage that they address, sometimes one process isn’t sufficient to automate an entire hiring process from start to finish. 

Namely, when filtering for specific credentials—hard skills and tangible qualifications like certifications and education or training backgrounds—these measure for only part of what you’re looking for in a candidate.  

But what about their resilience? Their problem-solving skills? Their leadership skills? Their interpersonal or social preferences in the workplace?  

Sure, your applicant went to an impressive school and worked at a wicked company before applying to your (even better) organization, but will they stick with you for the long haul, or will they leave you high and dry in six months at best? 

Personality assessments and other tests of these sorts can help resolve these issues, and even better, can be effective in measuring what is crucial to a position beyond the credentials and reference letters.  

With that said, some HR industry experts have found that aptitude tests and other tests of this sort can and often are cheated on.  

Experts in the HR industry have found that applicants can and often do “cheat” on their aptitude tests wherever possible.  

A study has shown that wherever possible, applicants will alter their responses and falsify information about themselves to ensure they make it to the next hiring round, and maybe even get chosen for the position, regardless of them genuinely being able to perform in that task or job function.  

This cheating usually involves responding in ways that would reflect the job posting—as in, answers you want to hear, rather than honest ones you’d actually give—and abilities that can be faked with knowledge taken from the internet or others helping them cheat.  

To solve this problem, I consulted experts at Self Management Group, and they were able to develop an additional aspect to their personality and career fit assessments that not only measure a candidate’s potential in a position based on their responses, but also the accuracy and consistency of their responses.  

From a simple online assessment, these experts can see how reliable a user’s responses were, and how confident they were in making their responses at the time of completion.  

This, it seems is the missing link to other tests, especially those that are measuring unique qualities that are crucial to a worker’s success in a position.  

My findings 

Ultimately, what my findings have all boiled down to is that no one solution I’ve tested out over my years of experience is sufficient to cover all of the ground needed to cover in our profession, and no one use of technology was able to automate my process effectively and fairly.  

So, of course, I built my own technology and platform to combine the best and most innovative technologies out there to create a comprehensive and automated system to filter and screen applicants faster and more effectively than any other.  

Why Workwolf

Workwolf is the accumulation of years of experience and the expertise of those in various fields of technology that can be used to improve hiring for the recruiter and the candidate.  

Our platform is comprehensive and allows recruiters and employers to automate their hiring process from start to finish with career fit assessments, customizable benchmarksexpedited background checking, and candidate bonuses like the Digital Work Passport, which empowers employees to own and maintain their personal verifiable and tamper-proof data for their entire career.  

And I know what you’re thinking: how can one platform do all of this? And is this really as good as it sounds? 

I’ll let you decide for yourself; sign up for free and try it out today! 

If you liked this blog post, you might also like Business and Management on a Budget: 5 Resources for Free Learning.”