Source | LinkedIn : By Oleg Vishnepolsky
I reckon the industry has about 2 years left in it, 4 at most. Machine learning, big data, propensity algorithms can deal with vast networks of connections much better than a human can.
Critical mass of the new tools, some of which are available now, will arrive by 2018 right when the next recession is predicted to occur. That’s when the companies and internal recruiters will start pulling back on the recruitment agencies fees, and using the new tools en-mass. Once on the tools, they are not coming back, ever.
The latest algorithms can predict when someone is ripe for a new job based on time in the job and social media activity, and even purchasing history.
The latest text analysis algorithms can pick out skills and experience much better than humans can, about 10 million faster.
In fact Microsoft has pretty smart algorithms in Azure cloud. They are buying LinkedIn with volumes of data and connections. Putting 2 and 2 together on what that means does not require algorithms.
Earlier this year LinkedIN bought a machine learning company with a specialty in AI recruitment: LinkedIn acquires recruiting startup Connectifier. So with help from Microsoft or not, LinkedIN is already on the way there. Judging by the number of machine learning experts employed by LinkedIN already they must be very close (according to LinkedIN search, search for “machine learning linkedin” on linkedin search).
After this article was published, LinkedIn responded with this insightful post:Making Hard Choices: The Quest for Ethics in Machine Learning. They are definitely working on this !
Please do not take my word for it – do a Google search on automation and machine learning with recruitment. There are companies that are already doing this algorithmic sourcing. The algorithms have been used in digital marketing for years now. What is new is the maturization of the machine learning field.
There are trends in the tech industry that are harbingers of a major disruption in the field of recruitment.