As we move further into the 21st Century, hiring practices are changing. There are very few industries which haven’t been touched by the technological boom of the past 20 years. Sourcing and hiring candidates, indeed all of human resources (HR), has been upended by the advent of new technologies.
Automation, including the use of artificial intelligence (AI) and machine learning (ML), are ushering in a new age of recruitment and hiring practices. These technologies are changing the ways we think about and approach HR, but also the manner in which candidates are sourced and screened.
What do these technological advancements mean for recruitment and what's their impact on HR and learning and development (L&D) departments when it comes to sourcing talent?
Robot Vera is an AI service which finds candidates, conducts interviews and screens resumes. The results are up to 10 times faster than traditional human interaction. The firm only started two years ago but already boasts big-name clients such as PepsiCo and L'Oréal.
Recruiters create a detailed job description which Vera utilizes to scour job sites looking for candidates. From there, Vera calls prospective candidates and screens them by using voice recognition to ask and answer questions about the open position.
Unlike a human recruiter, Vera can make thousands of calls a day, requires no sleep or breaks, and can do in one day what might take a human several weeks. Once completed, she sends recommendations on to the hiring manager for further review. If there’s a problem with the recommendations, hiring managers can alter the questions Vera asks to yield better results.
The true benefit in a system like Vera comes from taking the complicated and time-consuming legwork which many recruiters find bogs them down. Vera is available in 68 languages and appeals to a global marketplace due to the lack of time zone or language restrictions.
In a nutshell, it makes the recruitment process smoother and more efficient for global companies. However, the Vera method is more effective for sourcing candidates based on “hard” skills such as technical or education requirements. For executive and managerial positions which require a more diverse skillset, a human interviewer may still offer a better solution.
Saberr Base is an AI firm which predicts how well teams will work together. Founder and CEO Alistair Shepherd came upon the idea for the company while studying at Harvard University under Professor Noam Wasserman, who has stated that: "85% of venture-backed start-ups fail, and more interestingly 63% of those failures could be directly attributed to their team dynamics."
What Shepherd reasoned is that human resources are typically 70% of the costs of business and the major source of competitive advantage. However, hiring decisions are still driven by personal experience and gut feelings. By developing a system to apply data analytics solutions to hiring decisions, companies can make better-informed decisions.
Saberr works by establishing better team building practices such as communication, goal-sharing, and more. The results are data-driven choices which enhance team workflow. It is not a recruitment tool per se, though it does help screen candidates with surveys, profiles and test results. These results are then fitted to an overall candidate report which shows the risks and opportunities associated with hiring them.
As a result, the candidate report also shows how naturally the candidate will exhibit the traits and behaviors required of their position, in addition to how well they’ll fit into the existing team and culture of your company.
The company has seen successful implementation by large firms such as Proctor & Gamble, Charlotte Tilbury and the UK’s National Health Service.
Advanced analytics are inherently helpful in driving business process improvement. When it comes to recruiting, many of the AI-focused solutions are looking to cut down on the mundane tasks associated with candidate sourcing.
Take the example of Headstart, a recruitment app which helps to screen cover letters using machine learning models designed for the unique requirements of your position.
“At the moment some companies outsource the reviewing of thousands of CVs. Using Headstart, companies only have to review 100 CVs in ranked order of suitability, so we’re removing some of the more mundane tasks,” says Headstart co-founder Nick Shekerdemian.
By removing the task of slogging through hundreds of applicants, programs like Headstart allow companies to focus more of their efforts on vetting the top candidates. The result is a process which is greatly reduced in time while enhanced in quality.
However, many of these methods reduce or remove the human element from the process. What are the results? Does it yield better candidates and better hiring situations? This largely remains to be seen.
ThisWay Global is a recruitment service whose mission is to “use advanced technology to match people to jobs, not resumes to job descriptions”. More than a matching tool, it uses machine-learning algorithms to parse resumes and job descriptions and match candidates effectively.
The human element, however, is not removed entirely. This may help quell fears that robotics and AI will completely supplant human interaction in the recruitment and interview process. The technology has been shown to be effective in terms of sourcing and screening candidates, but humans have a better knack for interviewing and relationship building than machines.
Where then, can the human element be applied in AI and machine learning recruitment systems?
DeepSense is a San Francisco-based recruitment service that scans social media profiles of candidates to unearth personality traits. The company claims to use scientifically sound personality profiles to source and vet candidates based on their social score, emotional IQ, and more.
The service, in part, seeks to determine “the real candidate” by cutting through the resumes, cover letters and other details to determine and predict optimal behavior. However, there are concerns that such practices may lead to inherently biased practices. A single faulty algorithm may exclude otherwise viable candidates. There is also the real-world concern over privacy and transparency in hiring practices.
The practice of companies searching social media profiles is nothing new. It is part of a growing trend of companies assessing a candidate’s personality rather than the content of their resume. However, there is still more work to be done before a perfect pairing of human and AI elements yields ideal results.
Despite fears that AI will eliminate human jobs, we aren’t there yet. AI and machine learning algorithms can only go so far in the recruitment process, though expansion into these fields is occurring rapidly.
Tomas Chamorro-Premuzic, Professor of Business Psychology at University College London, believes the ideal situation focuses on a combination of both human and technology-driven solutions.
“The average computer-generated algorithm could probably outperform the average human judge when it comes to making interview decisions, so we could replace all human interviewers with digital interviews. However, the result would still not be as good as having really well-trained human experts analyze well-designed interviews with the help of computer algorithms,” he says.
The implication is that, as technology is further adopted, the need will come for the power of machines to truly approximate human ability. However, we’re not there just yet.
Until the time comes when machines can truly supplant human logic, reasoning and decision-making, recruitment will likely be left to the hands of qualified HR professionals. However, that’s no reason for companies not to take advantage of the available tools which aid that process.
If a Headstart, Vera or Saberr can maximize the efficiency of more mundane recruitment tasks, the result will yield better candidates and more streamlined recruitment processes. Researchers claim that for middle and higher skilled positions, machine learning and AI may enhance organizations’ ability to make better hires. However, they did not conclude that the process should be left entirely to the machines.
The future of AI and machine learning in the recruitment field will no doubt be impressive. As new technologies emerge, better processes will be developed.
For now, companies looking to make full use of available tools will have a leg up on the process. However, they are not yet a replacement for the human element in all screening and hiring decisions.