Whether it’s sorting through multitudes of resumes or social media profiles to find the best fit for a job, analyzing the vocal tone or facial expressions of job candidates in video interviews, or keeping applicants apprised of their hiring status, artificial intelligence (AI) is moving rapidly from experimentation to mainstream use in the recruiting world.
But what is it? AI is smart software with the ability to learn on its own and grow more effective over time.
Recruiters who view the rise of AI as a threat to their jobs may rethink their positions after getting a firsthand look at how this rapidly evolving technology can make their lives easier.
“There’s a greater level of maturity in AI tools in the recruiting space than in any other area of HR,” said Helen Poitevin, a Paris-based human capital management research director at Gartner, an information technology research firm.
Continued advances in AI will make tomorrow’s recruiting look much different from todays, but for now recruiters are hailing the technology for its ability to reduce the “grunt work.”
Rise of Artificial ‘Assistants’
Among the most evolved AI tools are artificial “assistants” that can help improve the candidate experience. One such tool is Mya, which automates much of the communication process with candidates during the application phase. Mya was created by FirstJob, a San Francisco-based HR technology company. Mya uses natural language technology to ask questions of candidates based on job requirements. It also answers applicants’ questions about employers and keeps them apprised of their hiring status.
Mya answers candidate questions on company policies, benefits and culture around-the-clock through SMS, Facebook, Skype, e-mail or through a browser window called a chat client where people can chat instantly. This saves recruiters from having to field these same questions time and again. If Mya is stumped, it contacts a human recruiter and then returns to the candidate with an answer.
“This kind of AI facilitates engagement with applicants and can help improve the candidate experience,” said Elaine Orler, founder and CEO of Talent Function, a recruiting consulting company in San Diego.
More emerging tools promise to remove these transactional tasks from recruiters’ plates, freeing them to focus on interviewing and closing job offers. One example of an application that may soon be part of recruiting platforms is X.ai, an artificial assistant that can schedule meetings or candidate interviews with no need for human intervention.
Such assistants are an extension of existing scheduling applications like Reschedge. It helps recruiters reduce time spent scheduling candidate interviews through an automated process that manages multiple calendars at once and is able to make updates if there are any changes.
IBM Watson Tackles Recruiting
Recruiters need look no further than the paragon of artificial intelligence, IBM Watson, to understand what’s possible in recruiting today. Watson brings new efficiencies to HR through applications that derive insights from vast amounts of data, continually build knowledge and offer personalized recommendations.
Watson can help recruiters measure the degree of effort required to fill certain job openings and help prioritize job requisitions, predict with accuracy the likelihood of candidates being successful and perform social media “listening” to create insights that help recruiters improve messaging to candidates.
Consider the process of triaging job requisitions. “Too often, it’s the squeaky wheel or the person pushing the hardest that gets his or her requisition addressed first,” said Bob Schultz, general manager of IBM Talent Management Solutions in San Francisco. “What Watson does is look across the pipeline, determine what fill rates have been and perform analytics against requisitions in the system to help recruiters decide which [requisitions] to focus on first—and explain why they should do so.”
AI Comes to Video Interviewing
Artificial intelligence also has made inroads in vendors’ video-interviewing’ platforms. For example, Boston-based Affectiva, an emotion recognition software company, helps gauge candidates’ emotional intelligence and truthfulness during video interviews by analyzing facial expressions, word choice, speech rate and vocal tones.
“Interpreting and inferring feelings based on candidates’ facial expressions is an intriguing use, but it is still early days for the technology,” said Poitevin. “Voice analysis is more evolved as a technology partly because there are more indicators that come into play, like how often people hesitate and the tone of voice they use.” Poitevin said vendors like Hire IQ are using voice analytics to aid recruiters in hiring workers for jobs like customer contact representative.
Qualifying Passive Candidates
New software also has emerged that helps recruiters predict how likely passive candidates will be to engage in a recruiting discussion. One such tool is EngageTalent, which combines news data with workforce data to determine the odds that people already holding certain jobs might be looking for greener pastures.
These “predictive availability signals” are based on factors like recent company performance or personnel changes. For example, EngageTalent could allow recruiters to search for “critical care nurses in Dallas with master’s degrees who work for health care systems that are closing locations.”
“This is the kind of AI where a lot of investment and innovation is happening today,” Poitevin said.
Other AI is expressly designed to make one aspect of recruiters’ jobs easier: identifying the best prospects from the many resumes or LinkedIn profile links they receive for job openings.
RAI from HiringSolved, a talent acquisition technology company in Chandler, Ariz., is an artificial intelligence assistant that uses natural language to interact with recruiters (similar to Amazon’s Alexa, a voice-activated virtual assistant housed in the Amazon Echo smart speaker). RAI asks recruiters what kind of worker they’re looking to hire, searches for available candidates and then helps recruiters refine the search. Once RAI has narrowed the list, it also can contact candidates by interfacing with recruiters’ e-mail.
Data Drives Effective AI
Data is the lifeblood of AI, and without large volumes of good historical data, software won’t produce the kind of insights or recommendations needed to elevate recruiters’ decision-making.
“The biggest barrier to true AI is lack of good data, and the biggest risk to organizations is not understanding the context of that data,” said Stacey Harris, vice president of research and analytics at Alpharetta, Ga.-based Sierra-Cedar, which conducts an annual HR Systems Survey.
“That’s why IBM Watson is so effective, because it has been sucking up quality data for years. The idea of who has the biggest database is important in the AI world, because the database is AI’s training model.”
But buyer beware.
Because AI analyzes and learns from patterns, there is a danger of the software replicating biases in recruiting or promotion processes, Harris said. For example, if a company’s highest performers historically have been identified as white males between 30 and 40 years old—because those individuals were frequently promoted into next-level jobs—that bias can inadvertently become built into algorithms that learn from talent management patterns.
“Artificial intelligence is only as good as the information it has been given to learn,” Orler said. “Without conscious thought involved to ensure we’re not perpetuating bad behavior, there will still be a need for humans to make final hiring or promotion decisions.”