Dymistifying AI in Recruiting

AI is the latest and most prevalent buzzword in the HR world with hundreds of vendors sporting some sort of artificial intelligence or machine learning within their product.  Due to the nebulous and changing nature of this technology, it’s making an already crowded HRTech landscape even harder to navigate!

With that in mind, we wanted to share some basics around how this tech works.  Interestingly, it’s actually been a part of the HR world for a long time (resume parsing, anyone?) but the sexiness of saying “AI” has become more and more important for various companies’ marketing strategies.  This is no doubt a byproduct of buzz around self driving cars and AI getting better at beating humans.

Here’s a basic overview on how this tech works, along with why humans aren’t in danger of losing their jobs anytime soon.  Big shoutout to Vinayak from Drafted for lending his expertise in this area (for a more in depth overview of this concept, keep reading below):

When we look at cool new tech in recruiting, we hear a lot about Artificial Intelligence and Machine Learning. Here are some of the keywords that you’ll hear thrown around, along with what these words actually mean:
  • Machine Learning: This is a very broad term that applies to systems that can improve every time they succeed or fail. For example, when you hit Thumbs down on Tinder, it uses machine learning to make sure that you don’t get that kind of a person again.
  • Artificial Intelligence: This is a very broad term that encompasses anything that a computer does where it’s trying to be as human as possible. This might mean making decisions like a recruiter, talking like a person, etc.
  • Keyword Extraction: This is a way of reducing normal language to just the words that are most important. For example, you might read a resume and think “ok this person worked at Facebook, they can program in Java, and their last job was as a Senior FrontEnd Engineer.” Keyword extraction allows machines to do the same kind of “30 second resume scan” that we do as recruiters
  • Ontology: This is just a fancy way of saying “this is how words relate to each other” – for example, we can look Software Engineering job descriptions and say that “Software Engineer” is related to “Java”
  • Bots: This typically is used as an umbrella term for “any automation.”
There you have it, a brief overview of AI and what you need to know at the beginning of your understanding of this space and how it can help in your recruiting efforts!  If you liked this content, you may want to check out other Whiteboard Wednesday sessions where we dive into topics related to talent pipelines, employer branding, etc.

 

Phil Strazzulla

Founder at NextWave Hire
Phil is a founder of NextWave Hire.Previously, he was a VC at Bessemer, and has a MBA from Harvard, and studied finance at NYU.