Why Humans Need To Be Removed From The Recruitment Process

Rectifying a flawed system

There’s a common concern that in the future, technology will take away jobs from humans — but what if it actually helps more people find jobs?

Companies like Deloitte already use artificial intelligence (AI) to help them hire in smarter ways, automating time-consuming tasks, reaching a broader selection of candidates, and eliminating bias. With these tech giants leading the charge, the use of AI is set to become standard practice in offices around the world. Still, there’s one obstacle blocking AI from performing at its maximum capacity:

Us.

Here’s why the future of recruitment needs AI and why that AI doesn’t need our human involvement.

Currently, hiring is an unfair, inefficient process. As human beings, we are naturally motivated to categorize people and objects — it’s normal cognitive behavior and makes us prone to biases. In fact, there are more than 140 cognitive biases, and even if we’re aware of them, we can’t completely separate personal opinions, experiences, and contexts from our judgement. That’s why there’s always space for discrimination in recruitment carried out by humans.

Research also shows that humans can only process 50 tasks at once. Yet in recruitment, there are hundreds of factors that need to be taken into account when sourcing people: education, experience, soft skills, hard skills, aspirations, location preference, certifications, network, and so much more. For many recruiters, the sheer volume of applicants for an open position — combined with the number of factors to consider — means that they naturally fall short in terms of accuracy and speed.

There’s also the realization that recruitment is heavily skewed in favor of the companies hiring. We often think of successful hires being a good match for the business and team, but what about the company’s suitability for the candidate? Too often, candidate preferences aren’t taken into account. Thus, what we’re left with is a flawed recruitment cycle — one where there are multiple entry points for discrimination, and one that is mostly centered around the hiring body’s needs.

Rather than depend on hiring managers, AI can identify all relevant factors in a company’s search for new talent. Granted, it’s a long list but it’s quantifiable and can be added to or cut as the business and recruitment process evolves. With this list, algorithms can be developed to capture the information around factors in the most representative way. Essentially, AI can determine the weight of each factor and use this weight to make a nuanced, calibrated prediction about how well-suited the candidate and company are to one another.

For example, recommendation weighting. With AI-powered recruitment platforms, people can give and receive recommendations in order to boost their job applications. Unlike conventional human recruitment, sophisticated algorithms look at factors such as the length of the relationship between the individuals, the number of recommendations a person has given, and even the type of language used in the recommendation. This data generates a weight (similar to a score), where the higher the weight, the more credible and relevant the recommendation is.

In this scenario, AI adds a layer of validation and transparency to recruitment. Companies don’t have to be aware of the possibility that recommendations are fake or misleading because the tech provides a clear scale around what to trust and what not to trust. AI can even detect spam recommendations and immediately discount them at the decision-making stage. This saves significant time.

It’s not just the screening phase that AI can impact.

Rather than schedule, prepare, and conduct an in-person or video call interview, AI can provide enough of a prediction about a person that an interview doesn’t need to take place at all.

AI can assess hard skills like coding, create tailor-made tests for applicants, and automatically review answers and highlight errors made by candidates. And because AI capabilities can be outsourced, companies have access to a much cheaper and less time-consuming candidate search. Likewise, from a candidate perspective, the hiring process is more streamlined without an interview as they don’t have to coordinate back and forth with recruiters.

AI doesn’t compromise cultural fit either. With data detailing specific personality traits and professional culture traits within a company, AI can produce a statistically accurate assessment of how well a person is likely to fit in a team.

Again, the tech is mutually beneficial because candidates ensure that their known traits are complementary to the role. For example, if the applicant avoids conflict but the position involves a degree of confrontation, they can be alerted of the disconnect. What AI is doing is giving both companies and candidates an instantaneous two-way check and a more in-depth analysis of one another - and all without an interview. This visibility is what will ultimately mean that more of the right people find the right work environment.

What’s even better is that in this context AI can help show where there are discrepancies that could actually benefit teams. If a department is missing certain skills, expertise, leadership styles or personality types, AI can quickly pinpoint applicants who possess these traits and alert recruiters to the most appropriate people to push the team forward. The speed and precision of this filtering are far better than any human attempt could deliver.

It’s important to note that AI isn’t only a tool that improves business operations; it’s also facilitating a more diverse recruitment sphere. In the unfolding remote revolution, if recruitment doesn’t modernize, there is the risk that existing prejudices when hiring will be exacerbated because people are physically siloed from one another. Any reservations about candidates could therefore manifest into a missed opportunity for both businesses and applicants.

In the past, for example, voice actors were asked to send photos of themselves to casting directors despite the fact that they were only offering audio as deliverables. In response, Voice123 — an open, online marketplace for voice actors — opted for AI as a fairer hiring alternative. The platform removed the possibility of discrimination based on appearance and built an AI-powered search for the global pool of voice actors. The result has been that voice actors are recruited for their talent, not their looks! The clear lack of bias has not only allowed voice actors to audition for jobs with confidence, but has also allowed the platform to flourish.

AI doesn’t need human perception or intuition — it scans and sorts, pairing people with jobs using professional criteria only. And because AI is trained on datasets that are more objective than recruiters, it can heavily reduce recruiting bias. It also doesn’t have the same margin for error that humans have. It’s extremely reliable and has the capacity to learn as it’s fed more data so as time passes, it will likely become even more advanced.

One research fellow in AI at IBM claimed that “AI has a shot at being better at decision-making than we humans are, particularly in hiring.”

The truth may be one step further: AI has already surpassed human decision-making. Until we fully remove ourselves from the picture, however, we won’t be able to experience it.