There are few things more tedious, yet at the same time more nerve wracking, than trying to find a new job. First comes the endless Googling, form completion and resume tweaking to make yourself look like the perfect match for every opening. Then once you make it to the next stage, it’s the dreaded job interview. The clammy palms, the dry mouth, the inordinate wait while you’re sat in reception. This is more often than not followed by wince inducing questions, “tell me about yourself”, “where do you see yourself in five years?” and the classic “what’s your biggest weakness”.
In short, the process sucks. Applicants have to spend hour upon hour, day after day, searching and applying for jobs, often repeating the same information again and again, while recruiters and companies spend ridiculous amounts of time and money working with a broken system.
But what if common household AI tech like Amazon Alexa, or Apple’s Siri could take all this off your shoulders, while making the process much more straightforward for all involved.
Why is the current system so flawed?
The ever more competitive nature of the labour market, driven by factors such as immigration, growing educational attainment and our globalised workforce, mean recruiters are swamped by applicants like never before. It’s therefore no surprise to hear that half of the recruiters surveyed in a recent study said the hardest part of their job is identifying the right candidates from a large application pool.
Not only does this deluge of applicants make sorting the wheat from the chaff more difficult, it creates other problems as well. The more applicants a recruiter has to assess, the more time and resource they have to commit, and the more time and resource they throw at something, the more it costs.
Once the recruiter has whittled down the list, while hopefully not overlooking any talented applicants, comes the next major flaw, the interview. People who do well in interviews are often people who are skilled at talking a good game when under pressure. Unless the job is for a sales position, auctioneer or talk show host, this provides the recruiter or hiring company very little actual proof that the candidate can do the job they’re applying for.
Recruiters are all too aware of these problems, and since the 1980’s have embraced psychometric testing as a way to cut through the waffle. However many consider these to be flawed, creating more problems than they solve. Applicants will often answer questionnaires based on how they think they should answer, rather than being truthful. While others see an unintended side-effect of these test as weeding out any diversity from the application process, damaging an organisations creative ability along the way.
And what about the other side of the fence, at the applicant level. I’ve never met anybody that realishes the job hunting process. While some people have the gift of the gab and can breeze through even the toughest of interviews, nobody enjoys the tedious admin of online form submissions or long winded multiple choice personality tests. All of this takes time, which if you’re already working in a full time job and have a family, can be very difficult to find.
Then there are the psychological barriers that many applicants face. It can be daunting for some people when speaking to recruiters or hiring managers at the initial recruitment stage, not to mention the actual interview itself. Or maybe the applicant’s personality wasn’t deemed the right fit yet their skills were a perfect match. Worse still, the applicant could be the subject of hiring bias, where their gender, ethnicity or even their name may count against them.
Tech to the rescue?
Thankfully, it looks like tech could fix many of these issues. Software developers are now busy designing AI and algorithms that can read and understand, at a deep semantic level, the content of applicants resumes, which is greatly improving the speed and efficiency of the shortlisting process.
In addition to these backend processes, AI is also taking a more hands-on approach with applicants. Chatbots are now being used to pre-screen candidates and answer any questions they may have about the job opening. This is saving recruiters time, allowing them to focus more on talent acquisition instead of being burdened with basic admin.
The traditional interview process is also being challenged as the best way to select a candidate. Rather than relying on 90 minutes of exaggerated achievements and boastful accomplishments, tech companies are developing deep learning programs as a way to assess the talent and potential of candidates. This is being assessed through highly adaptable cognition tests and real world simulations.
What the future may hold
While these innovations may well be great for recruiters, it doesn’t address some of the issues faced by applicants. While chatbots may relieve recruiters of some of the more tedious aspects of their jobs, it doesn’t relieve applicants from the hours of job hunting and form filling in. So what innovations could be around the corner, to fill the applicant-tech deficit?
A good place to look for answers is at an industry that is, somewhat surprisingly, often to be found at the forefront of consumer innovation. The insurance industry has been quietly leading innovation for decades in the consumer space and is now expanding rapidly into the virtual assistant space.
Insurance is now one of the leading industries developing within Amazon skills, the developers area where third parties can integrate services and features into Amazon’s Alexa service. A number of insurers are now offering quotation services through Alexa’s voice command service.
This provides a great example of where recruitment tech could be headed, from the applicant side. The insurance services work on Alexa by holding a range of data variables that are required in order to perform a risk assessment, to then provide a premium calculation.
The principle is not that different from a job application. The applicant has to provide data for a number of variables, which the recruiter then assesses to make a decision. If recruiters are now using AI to screen applicants, why not have applicants use AI, to screen for openings and submit the application in the first place. And if applicants sync their Linkedin accounts, they wouldn’t even need to manually input any data.
And just as Alexa can now automate an insurance renewal each year, why not let it automate a job search at certain times of the year such as just before an annual salary review is due, so employees can benchmark their current market value.
But even more startling are the other possible applications of this technology during the job application process. AI and virtual assistants are now being used to interview candidates in some instances, with only the very last interview stage being a human-to-human conversation. This then raises a profound question, if recruiters are prepared to let virtual assistants talk to candidates, why not let the candidates virtual assistants talk to the recruiter or their tech.
While virtual assistants are still in their infancy, the user data held by the companies developing them are anything but. Cortana, the virtual assistant developed by Microsoft knows every internet search you’ve ever performed while Apple’s version, Siri, can read every imessage you’ve ever sent or received. Such a wealth of intimate personal data means the tech providers behind these personal assistants are now a much better judge of a candidate’s personality, temperament, or in some cases ability, than a psychometric test or 90 minute interview could ever determine.
However, while the technology may be just around the corner, the bigger question could be consumer acceptance. Would people be happy to let some of their most intimate digital data be analysed and used to inform a virtual assistant when applying for a job on their behalf. Or could the brutal honesty of this system be the biggest turnoff for applicants, try to imagine a world where it’s impossible to exaggerate in a job application. But perhaps we won’t have to imagine that world for too much longer.
