3 min read

She is Helena. She is virtual – a robot, yes – a matchmaker that uses AI and machine learning to connect the right candidate for the right job opportunity.

The bot goes further. After scouting the best candidates, and matching them to available roles, she (that’s the gender inventors decided upon) approaches them on behalf of the organizations.

In other words, a full-fledged corporate headhunter driven by artificial intelligence. Or you may call it a simplified job-hunting tool from the other end. In essence, the AI-powered virtual assistant plays the dual role, serving not only as a company headhunter but also as job seeker’s agent, meaning both sides do not have to search for each other.

As an AI agent, Helena allows professionals to discreetly and ‘passively’ receive job opportunities from companies. Once the candidate shows interest, she refers them to the company and ensures they respond as quickly as possible.

It has taken the AI startup Woo over two years to build Helena, putting together what they call a ‘dream team’ of the best recruiters and data scientists from industry-leading companies such as Google and Facebook, other than the top algorithm engineers from the market.

And while it takes real stuff to train the ‘unreal’ headhunter robot how to think and make decisions like human recruiters, Helena has got smarter over time through employer feedback and machine learning. According to the company, she is out-performing human recruiters in the quality of her match-making and the speed of her performance. She is “constantly calibrating and fine-tuning her decision-making based on the client’s dynamic needs and feedback.”

“If you think about an interview, it’s an outcome of a lack of information on both sides,” Woo CEO and founder Liran Kotzer says. “But if there’s a machine that knows everything—like a god—knows about your past experiences, about your projects, your culture—the machine is going to tell you that there’s a perfect fit and both parties won’t question it.”

So are the Helenas going to totally disrupt the future of recruitment? There are both sides of the argument. But you can’t take away the fact that the AI assistant is infinitely scalable. Unlike her human counterparts, Helena has the capacity to handle an unlimited amount of candidates. Free from individual views and biases!

That qualifies as fair – up from fair enough – in terms of selection criteria. Here, your candidature is considered based on scientific algorithms considering your past success, trends, CTQs, and metric-based relevant data sets. It has a potential of bringing a new era of transparency.

“Helena turns the tables on today’s labor intensive and largely unscientific recruitment process. Unlike using an expensive headhunter to manually source and screen a limited number of candidates for specific jobs, Helena uses data science to hire,” Kotzer adds.

Connecting possible employees with their would-be employers – without the intervention of either – is too much of an automated concept. But the start has shown remarkable accuracy in the matchmaking. Woo claims its headhunting software has a 52 percent success rate of interested candidates accepting job interviews. That is nearly twice that of human recruiters, isn’t it?

For people on both sides of the interview table, the hiring process is tedious. There are stacks of resumes, cover letters, supplementary documents, LinkedIn profiles, and countless job interviews. It makes a definite sense to automate the repetitive tasks if we have the requisite analytical insights for the data leading to optimized job matches.

That prepares the perfect ground for artificial intelligence to take over. You would not call Helena ‘just another bot’ for at least attempting to solve the age-old problem of recruitment bias.

Writes and reports on lnformation Technology. Full stack on artificial intelligence, data science, and music.


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