We’re all familiar with GIGO: “Garbage in, garbage out.” That holds true as much for data as (sorry to say) the human-resources supply chain. The quality of your company’s output depends on the quality of the people you put in it. So it’s imperative to find the people best qualified not only for the technical demands of the job (the hard skills) but also for the social demands of a well-functioning team (the soft skills).
Hard skills naturally lend themselves to automated evaluation. But it hasn’t always been clear that machines could evaluate people’s soft skills.
While human judgment will likely remain a necessary complement to AI, we’re seeing the proliferation of AI throughout our lives because algorithms outperform humans in so many fields of endeavor. So just as artificial intelligence revolutionizes everything it touches, it’s now revolutionizing the human-resource supply chain.
AI is an insatiable learner. The more data you feed an AI application, the better its output. And the design of AI, particularly adaptive intelligence, often emulates the design of the human brain. Adaptive intelligence is “a branch of artificial intelligence dealing with training neural networks, where the objective is to program how the system is to interpret information and react rather than to program how a system solves specific problems.” As described by Oracle, adaptive machines “collect and analyze data to help automate transactional processes and decision making in smart ways that learn, adapt, and interact, based on experience.”
AI heating up
According to CareerBuilder research published last year,”more than half (55 percent) of HR managers surveyed say AI will be a regular part of HR in the next five years. Already, 1 in 10 HR managers (13 percent) are seeing evidence of AI in their work.”
Companies in that space include Arya, the AI recruiting tool from North Carolina-based Leoforce, and Mya Systems, which announced $18M Series B funding in 2017, as well as Restless Bandit, Gloat (until recently known as Workey), and talla. HireView’s Video Intelligence system is a state-of-the art approach to pre-hire candidate assessment. Avatar simulation like the kind developed by Mursion for training simulations has potential well beyond onboarding. These companies are among the many “white-collar automation” enterprises featured in CBInsights’ market map in their report, “Top AI Trends to Watch in 2018.” The report briefly summarizes 13 AI trends affecting white-collar professions such as lawyers, journalists, wealth managers, and HR. The game has always been all about identifying high-value candidates whose skill sets dovetail with the demands of the job. The stakes are just a lot higher, and investment in AI overall continues to heat up.
According to research reported by the Kelly Outsourcing & Consulting Group, “experts predict that between 2016 and 2021, revenue for talent acquisition technologies will rise at a CAGR of 14.6 percent. In 2021, the total global revenue for these technologies will amount to approximately $6.8B.”
Market analyst Laroque.com reported total venture capital for HR tech alone in Q4 2017 hit $1.064 billion.
How AI assists talent acquisition
Capturing a true snapshot of a candidate can be messy and prolonged. AI can accelerate the entire human supply chain and add cost-saving efficiencies at every stage, as noted by such writers as Vartul Mittal, writing for Medium, and Joseph Steinberg with Inc.com:
- By automating resume screening, candidate interviewing and background screening, AI can reduce human bias (although some observers have reservations).
- AI applicant-tracking systems can improve compliance through their efficient data-matching capabilities.
- It can enhance candidate assessment by adding an AI layer to human engagement.
Virtual reality is no longer a thing of the future. VR and augmented reality continues to make important inroads into employee training taken broadly, whether in law enforcement, medicine, retail, or practically anywhere else.
As a subsidiary of CastleBranch, a global leader in background screening and compliance, tekMountain grasps the benefits and efficiencies of AI-enabled screening as part of its broad research into HRtech, medtech and edtech. We know that candidate screening and interviewing are special cases. On one hand, true identification, from a compliance standpoint, remains critical, yet the soft-skills component of a good candidate until recently often escaped automated evaluation. Not so any more, if current developments continue apace.
Chatbots and virtual personal assistants were just the beginning of AI-assisted user interaction. But current developers are making enormous inroads upon improving the chatbot.
Affectiva’s emotion AI was spearheaded by computer scientist Rana el Kaliouby, who started out trying to find a way for people to develop new relationships with their technology in order to maintain (sometimes restore) their emotional relationships with real people. Her TED talk, watched by more than 1.4 million viewers, showcases a facial-recognition demo app that has clear applications for HR video interviews. Beyond facial expressions, AI is helping recruiters makes sense of speech patterns and micro-expressions that tell us much about one’s emotional intelligence.
But there will always be a place for the human recruiter. “Recruiters will continue to be the lynchpin for organizational success even as bots, artificial intelligence and automation increase in usage, said Caroline Stokes, founder and CEO of both her recruiting agency FORWARD and the Emotionally Intelligent Recruiter. “We need to work in harmony with artificial intelligence,” she said. “Tech cannot replace the human experience. In fact, it’s never been more important to be human.”
Advantages of AI-enhanced background checks and applicant tracking are varied:
- Speed of operation. One look at the enormous backlog of U.S. government background checks tells us that speed to completion is urgent.
- Volume. Always there are many times more applicants than there are open positions and recruiters to process applications.
- Reach. Candidate data exists in multiple locations across multiple online platforms, a challenge that’s fully within AI’s wheelhouse.
- Depth. The depth of research possible with AI can help to reduce risk by checking into candidates’ prior affiliations and employment and to flag potential conflicts of interest.
- Relevance. AI is proven more capable than humans in filtering out non-relevant data from enormous data sets.
- Timeliness. Too often, good candidates kept waiting are lost to recruiters. The whole of these components—timeliness—is far greater than the sum of the parts.
Will AI replace humans in the HR space?
Not likely. Some jobs are improved by automation, others by augmentation. The latter requires the kind of judgment and control in which humans—so far—are unexcelled. So, as Artur Kulian argues in Entrepreneur, we must focus on the importance of making employees AI literate: “Companies should emphasize the human component in technical jobs and create a balance of technical skills and more general purpose skills like creativity, social skills and emotional intelligence in their workforce.”
Let tekMountain show you how we can help synergize your AI enterprise. Call today.