Finding the Next Rockstar Employee: How AI and VR are Changing the Hiring Game

By Lisa Rabasca Roepe, Contributor

The days of recruiters sifting through piles of resumes may soon be over as machine learning, AI, and VR make their way into the workplace, helping companies find the best available talent.

By aggregating available public information, such as social media feeds, LinkedIn profiles, and YouTube videos, recruiters can better understand a candidate’s skills, competencies, passions, traits, and career interests. This is becoming increasingly important, as recruiters are expected to evaluate candidates on more than just how they will perform in the position in question.

According to Brianna Foulds, director of talent acquisition at Cornerstone OnDemand in Santa Monica, California, recruiters must also determine how well a candidate will fit future roles. The root seems to be the current resume format that is an outdated method for assessing potential hires for future roles, she said.

“Many companies would love to see a departure from the current format that simply lists skills, experience and education, and instead shares detailed information about actual projects that candidates have worked on and completed,” Foulds explained.

The Candidate at Large

According to Foulds, companies want to know more about the candidate’s personality, how he or she will interact with other employees, and how well they have collaborated on a team.

Today, companies are finding ways to use emerging technologies, like artificial intelligence, to aggregate a candidate’s social media feeds to do things like verify completed courses, languages spoken, and previous positions. These emerging technologies could also show a dashboard of how former managers and colleagues rated the candidate.

This type of data would allow companies to sift through resumes to identify the top candidates by matching not just based on job description keywords, but also the candidate’s experience, credentials, ratings, project outcomes, and their social media persona.

Companies have already begun using machine learning and AI to create these types of algorithms. In February, Frrole, Inc., a Palo Alto-based social intelligence company, released DeepSense, an AI tool that uses public data to predict how well a candidate will fit into a company’s office culture. By assessing the applicant’s Twitter activity, LinkedIn profile, Instagram posts, and blog articles, DeepSense can evaluate things like whether the candidate is outgoing or shy, and how well the candidate might get along with current colleagues.

But the DeepSense algorithm doesn’t just identify matches for current skills; it also evaluates how well a candidate can adapt and evolve over time. Candidates are evaluated on their ability to learn, attitude and outlook, need for autonomy, and teamwork skills. The tool enables companies to assess a candidate’s attitudes without requiring the candidate to take a 30-minute personality test, said Amarpreet Kalkat, the company’s co-founder and CEO.

While Kalkat doesn’t see DeepSense replacing resumes, he does believe it will give recruiters and hiring managers more insights about candidates earlier on in the process. Companies often don’t assess for culture fit until the end of the interview process, but this method would allow recruiters and hiring managers to address a candidate’s cultural fit and personality before the first interview is even conducted.

“Why waste time on candidates that might not be a good fit?” he asked.

Beyond the Org Chart

Machine learning and AI are also taking on more tactical assignments, enabling recruiters to focus on responsibilities that need a human touch. For instance, more recruiters are using bots to compile data about candidates, to schedule interviews, and put together offer letters.

“[Bots] are allowing recruiters to focus on finding the right person by taking away administrative tasks and instead allowing [humans] to interview a selection of people, identifying the right person, and advising managers,” Foulds said.

Meanwhile, the Institute for the Future’s Emerging Media Lab in Palo Alto is exploring another aspect of hiring: understanding how colleagues interact with each other so managers know what skills to hire for when replacing an employee.

In 2018, the idea goes, the standard organizational chart doesn’t capture relationships between colleagues or reveal how employees collaborate, Toshi Anders Hoo, director of Emerging Media Lab, explained. Yet by combining an org chart with survey data that asks employees who they typically work with, who actually offers support, information and career advice, and who helps create innovative solutions, the company gets a more holistic understanding of employee structure and management.

Using the survey data and current organizational chart, the lab is developing a virtual reality system that represents the relationships between team members so hiring managers and recruiters can visualize how employees interact and collaborate, not just who reports to whom. Emerging Media Lab’s aim is to give companies a better idea of how work gets done and what specific skills and personality traits are needed in each role to foster team collaboration.

All of this additional information—social media content, personality traits, and the ability to learn, adapt, and collaborate—will help recruiters and hiring managers to find the best employees to fill current positions as well as future roles. “This type of information will become even more critical as people move from employer to employer, and work for shorter stints with each company,” Foulds says, adding, “[The] information already exists. The difference is how the information is organized into a format employers can use to make hiring decisions.”