It’s no secret that technology and automation have permeated nearly every aspect of the recruiting industry over the last two decades. So, it shouldn’t come as a surprise that organizations are relying more and more on sophisticated automation systems and algorithms to wade through the masses of resumes they receive on a weekly basis.

Google alone receives 50,000 applications a week. Without automation to narrow the pool, even its well-resourced hiring team would seriously struggle.

With this extreme example in mind, have a look at some of the pros and cons of using technology to improve efficiencies in hiring.

Narrowing the Field in a Few Clicks

In the case of Google’s massive intake of resumes, Google immediately trashes nearly 60% of them due to spelling mistakes and typos.

With the availability of software like Grammarly and inbuilt spell checks, it’s not surprising that Google takes this stance. If a candidate can’t be bothered to run these few last checks on their resume, then they are not the type of candidate Google is seeking.

Your company may also take a hard line on resume mistakes, not necessarily because you agree with Google’s viewpoint, but because it is certainly one way to narrow the field of candidates. Technology can now do the ‘proof-reading’ for recruiters, so it is a quick (although not necessarily scientific) way to reduce the applicant pool without any additional effort.

The downside of cutting nearly 60% of your applicant field based on spelling errors and typos, however, is that you are whittling away potentially qualified candidates who may have been able to bring a great deal to the company, but, for whatever reason, failed to notice and rectify a minor error. In some cases, it may not even be an error – it may be a stylistic ambiguity. Grammar and punctuation, for example, should aid communication, which sometimes means bending grammar rules.

Google can afford to be fussy. Not all companies can. And if they want to avoid missing out on talent, it may pay to be more forgiving in this regard.

Removing Human Bias

Psych 101 tells us that humans are innately biased, whether they are conscious of this or not. That means recruiters and hiring managers will tend to pick out candidates who are more like themselves and reject those that are not.

There may be some value in this if “cultural fit” is a priority. However, studies have also shown that more diverse workforces tend to be higher performers. They have lots of different people with many perspectives on how to solve problems. Not to mention that customers often prefer to work with companies that hire diversely, because this is a better reflection of the real world and shows a company’s commitment to embracing all genders, races, and creeds.

By using algorithms to assess candidates following a series of psychometric and personality tests, companies like Google, hire staffers that tend to be a better fit and stay longer in the organization than companies who only use human resources to hire.

While the evidence backing up the use of psychometrics and other candidate testing is compelling, most hiring managers would argue that they still need to meet and assess candidates in person to determine whether they are a “good fit.” Humans are very instinct-driven; rarely more so than when they are evaluating another human who they have just met.

By delegating the “judgment call” aspect of hiring to a machine, the door opens to hiring remorse. Especially if the hiring manager sensed something was “off” about a candidate during the interview process, but chose to override their gut and hire them anyway, simply because the candidate aced all of their tests.

For the foreseeable future, it seems prudent to combine the increasingly sophisticated technology available with human input when it comes to candidate selection. Balanced hiring is possible when humans use data and automation to aid their decision-making without feeling the need to be ruled by their technology.