Written by John Gwinner
Today, unemployment is at a record low, yet according to Glassdoor, each corporate job offer attracts over 250 resumes. If a recruiter read these in depth, did internet searches to validate the resume, and scanned professional sites for connections, they could easily spend months looking for the right resume.
A human cannot handle this deluge. Cue the computer.
Artificial Intelligence. Everyone thinks it means something different. Many people think it means living, thinking computers. Like the old saying: “The amazing thing about a dancing bear isn’t that it dances well – it’s that it dances at all.”
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These recruiting systems do use a primitive form of AI; typically, resume scanning for certain keywords. These have been the bane of job seekers everywhere; a friend was rejected because they didn’t have “Social Media” even though they liked their key skill, “Social Media Marketing.”
The bear does not dance well. The fact that it dances at all saves us from being buried, so everyone uses these systems, while at the same time despising them.
A few years ago, at the Game Developer’s Convention, at the AI roundtable, I remarked that I’d be happy if we had Artificial Stupidity. I mean, stupid would be if someone decided to offer me a CTO job in NYC if I had “cannot relocate” on my resume, but was otherwise a perfect fit (I live in SoCal).
At this point, I’d take that job. Sometimes, we can all use a little stupidity.
When I was in the Marine Corps, one of the “Jodys” that we called to keep in time running, had a stanza that I’d rarely heard anyone else call. The punchline of that stanza was “To show the world the brains we lack!”
It’s not smart to charge up a sandy beach with bullets whizzing past your ear. Just because you aren’t smart, doesn’t mean you’re stupid.
Newton isn’t smart to jump into the recruiting fracas. There are billions of resumes and jobs floating around. How do you sort through it all? They would have to be crazy.
Crazy like a fox.
How do they sort through it all? Via their new AI algorithms, they sort through it well.
Back to what most people think AI is: it sounds like an artificial intelligence; someone smart, that is fueled by electricity instead of Jolt Cola and Hostess Twinkies, like those developers under the desks keeping the economy going.
It’s not: it’s more like your toaster. Not hot enough? Heating filaments on. That’s it. AI requires very narrowly defined problems, usually expressible in a series of numbers. One of the popular AI training algorithms looks at flowers. They reduce the Iris down to four numbers; the width and length of the green parts and the pretty parts. These numbers get added up, and out pops a Virginia iris.
Computers are very fast at adding up these numbers perfectly. If we can reduce difficult problems to a series of numbers, computers can help give us the answer; it’s only as good as the developers behind it.
At the end of the day, it’s number crunching. Do you use Linear Regression or Gradient Descent? NLP (Natural Language Processing) can scan for meaning, not just keywords, but takes a long time if no words match. Where do we draw the line? You need someone pretty smart to figure out how to crunch those numbers.
Newton.AI has some very smart developers.
It’s all very empirical. You’ve got to spend the time with the data, going through it, running the analysis. Where do companies tuck away their job listings? Is it fresh or stale? Where is the right point to bring in NLP? That analysis is exhausting.
Yet, it started simply enough.
Helder Silva, CEO of Newton.ai, was a clinical researcher in a hospital pursuing his Ph.D. when he met his Co-founder, Rui Costa, at a Hackathon organized by Microsoft in Portugal. Rui, who at the time was finishing up his degree in Software Engineering, mentioned that “AI would be a gateway towards a fulfilling future.” They noticed that the youth unemployment rate in Europe was rising, with some countries reaching close to 45%; yet also there were substantial employment vacancies. There was a distribution problem and a mismatch between job seekers and companies, masked by the sheer quantities of resumes involved.
Now seeing the problem, Helder and Rui brainstormed solutions. They continue to refine their algorithm that reacts to the fluctuations of the market in real time and builds an efficient distribution model to balance demand and supply. The right candidates can be matched up with the right company, efficiently and effectively, saving time and money for all.
Newton.AI has done this exhaustive analysis. They don’t just rely on AI; they also personally review and hand curate every applicant. Their AI lets them concentrate on a smaller pool of higher quality experts.
As Helder says: “Recruitment will be completely reshaped by AI, and this will lead to a better and fair future for job recruitment, that is not biased in race, ethnicity, gender, age, or beliefs.”
Shouldn’t you put that to work for your recruiting needs? Isn’t it time for the bear to dance well, and quickly? Newton can deliver hand curated experts that are a fantastic fit within 48 hours of an opening. Can your recruiters do the same?