How is machine learning changing recruitment?

Machine learning might be an unfamiliar concept to many people, but the principles behind it are quite straightforward.

Instead of giving a computer direct programming to achieve an outcome, you feed it a database of past results and use a learning algorithm to predict what will work in the future.

For example, if writing a song, you might ask the computer to analyse recent pop music hits and tell you what key and tempo sell best, how many verses and choruses to have, and so on.

Machine learning is particularly well suited to complex human interactions, ranging from marketing to recruitment, as it allows computers to apply their full processing power to the problem, not limited by the thought processes of the human who programs them.

Machine learning in recruitment

The potential applications of machine learning in recruitment are vast, especially considering the huge amounts of data that are now available about potential candidates on social networks from LinkedIn to more casual platforms like Twitter and Facebook.

By running the candidate’s profiles and posts through complex algorithms, computers can identify patterns that a human would never spot, and flag up the individuals who would be likely to thrive in the role, based on which of their predecessors performed the best.

Speed is of course a major factor in this, as computers can do all of that much faster than a person can do it by hand, and in this way you get a head start over the competition when an especially capable candidate expresses an interest.

This doesn’t mean recruitment is automated, by any means – there are still a great many human interactions that go into negotiating the best salary for both candidate and employer.

However, machine learning is helping to streamline the early stages of the process, ensuring that only high calibre candidates are put forward for each role, and increasing the proportion of interviews that end with the candidate getting hired.

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