Why AI Doesn't Mean Taking The 'Human' Out Of Human Resources

by Georgene Huang

 

Artificial intelligence, commonly known as “AI,” is a popular buzzword these days. Some of us hear the term AI and picture of a dystopian future where people lose jobs and control to robots who possess artificial — and superior — intelligence to human beings. Others are more sanguine about our ability to control and harness technology to achieve more and greater things.

 

While it’s impossible to predict how exactly AI technology and capabilities will evolve, the fact of the matter is that AI is no futuristic science fiction; it is here today in many forms and manifestations. And AI exists in areas you may not necessarily think it does — such as in HR departments where the technology actually helps place people in jobs rather than make them redundant.

 

I recently spoke to Brett McCoy, head of Employer Brand and Recruitment Marketing Strategy at Alexander Mann Solutions, a leading recruitment process outsourcing company. He explained how his firm offers AI solutions to solve human resources challenges and problems.

 

McCoy told me, “My colleagues and I believe that AI, when applied properly and under the proper strategy, will deliver candidates an exceptional experience [and help ensure] hiring managers they are getting the best [job candidates]...AI, and automation in general, should not simply be looked at as a replacement for people in the hiring process, but instead, [as helping to] move people (recruiters) from repetitive tasks to having more candidate conversations and building long term candidate relationships."

 

In short, McCoy believes that AI is a tool that more companies could put into place to help them (a) automate repetitive and mundane aspects of the recruiting process, (b) improve the job candidate experience and (c) improve the candidate application experience, in part by reducing bias during the recruiting process. He gave me three examples of how Alexander Mann’s clients leverage AI technology today to do just that.

 

First, we discussed resume parsing based on machine-learning technology. Consider the fact that at a small company, an employer may put up a job posting or requisition and then look through in-bound resumes to see who should be interviewed. At a slightly larger company, an employer may both post more job openings as well as interview more people, which means they employ a larger team of HR professionals. At some point, however, some companies receive so many applications for such a multitude of job openings that the task of simply sifting and sorting through those resumes becomes overwhelming.

 

Today, applicant tracking software (ATS) helps alleviate the burden of a talent acquisition professional having to look through every single resume. Users of ATS systems can search through vast amounts of resumes and applicant data by keyword, education, location and years of experience. However, as any internet user knows, even a very good search engine doesn’t necessarily make you confident that you’re seeing the most relevant search results.

 

This is where AI comes in. Using machine learning technology, employers can feed a system teaching sets and information about who the top current employees are for a given open position, providing resumes of top existing performers, their backgrounds and career paths. Resume sifting with an AI layer means that candidates matching certain criteria (e.g. location and previous job title) can be ranked and presented to a recruiter based on other desired traits or backgrounds that match top performers among current employees.

 

The implication, of course, is that there is a potentially much better outcome for the hiring manager and employer in terms of candidate fit. While a human being would still meet and interview highly ranked, suggested candidates, it’s clear that this kind of technology could make the recruiting process much more efficient and successful.

 

In addition to solving a candidate volume problem, AI also has the ability to prevent an over-abundance of poorly matched job applicants in the first place. McCoy explained, for example, that some of Alexander Mann’s clients employ chat bots to help prospective job seekers get the information they need or want to know that simply isn’t available in a job description. McCoy told me that chatbots can be used to help job applicants understand whether they can keep their social media profile if they take a job or how flexible an employer is — before they even apply for a role at a company.

 

In helping to disseminate personalized information at scale, chatbots for applicants can help create a better experience for job candidates, empowering the individual to make better decisions in a personalized way. Moreover, any company using AI to sift through and rank massive numbers of resumes can intelligently communicate to prospective job seekers that their application is no longer being considered — as opposed to simply not responding to the job applicant or “ghosting” them.

 

Last but not least, McCoy explained that he believes AI can help eliminate bias and unconscious discrimination in the interview process. With AI, job applicants are ranked by objective information, as opposed to an interviewer’s “gut” or intuition.

 

After a resume has been selected, AI can be leveraged into video technology to facilitate an initial screening interview. Video interviewing technology can help an employer analyze whether an interviewee was likely comfortable (or not), whether there may be an issue with an interviewee’s level of honesty, and it can even grade the quality of the answers to questions given to an interviewee. While a report from a video interview may not be the only thing a hiring manager relies on in making an employment decision, it can help eliminate a lot of wasted time and limited recruiting resources.

 

As an employer and a hiring manager myself, this technology all sounded quite promising — so I was somewhat surprised that McCoy believes AI is not very common within HR departments. Part of the reason lies in the inherent cost of such technology. While there are an increasing number of players and vendors entering the HR space with AI tools, the cost of processing that much data can be high for a company with a high volume of hiring needs. Moreover, there can be initial distrust of AI replacing human judgment, or simply the difficulty of implementing new processes and workflows into an HR department.

 

In some cases, AI-driven efficiencies within Human Resource departments could eliminate the need for as many roles in the talent acquisition department. However, it was clear to me after talking with McCoy that AI is just as likely to be used to free up human resources departments to focus on higher level, meaningful activities , such as helping to improve a company’s employer brand; creating programs and initiatives to retain the best, most qualified people; or to simply providing other services such as training or learning and development.