Talent Industry Trends

Machine Learning in Recruitment Space

By February 12, 2020 February 27th, 2020 No Comments

It has been fun when we are asked questions such as

A. How do you “stack rank” candidate profiles? or

B. How do you represent match-score between Job Description and Resume? Our answer to it is that Turbohire does not do any of two !

What has started to worry us are use cases of AI, where user accepts, or worse, acts upon the cause-effect relationships assumed by algorithms based on machine learning without understanding them.

The fundamental reason for this worry is the way two words “Artificial Intelligence” and “Machine Learning” are causally thrown around these days, used as synonyms of each other, even though they are quite different. People in recruitment and HR function are no exceptions to use them liberally.

We human beings are intuitively adept identifying patterns and apply knowledge of learned patterns for immediate/ future decision making. Computers can also observe patterns and apply them in their decision making without ever understanding the conscientious logic/ purpose behind them. Google Translate is one such ML system, which understand neither of the languages or purpose of communication.

We call this approach “Mimicking”. This works reliably when same things happen reliably over and over again and there are no changes in the environment, such as in Chess. But in the real-world of recruitments, candidates and companies both are always evolving and changing.

Lately, the thrust of Machine Learning or “Mimicking” has gone in direction of Big data, in which powerful computers ingest massive amount of data and look for patterns. The thing to get deeply concerned about is that “Mimicking” or its decision rules in recruitment space are somehow widely believed (because now it is based on even bigger data) and because they are widely believed they are widely used. It has only started to surface that applying “Mimicking” in evolutionary eco-system of recruitment can be dangerous because of things indeed going wrong at Amazon and other places. On a lighter note, “Mimicking” though by itself is an art form, at times it falls flat, or other time may be construed in bad taste.

Remember that computers while “mimicking” have no common sense. For example, a computer could easily misunderstand the pattern that people wake up in morning and then eat breakfast to mean that ‘waking up’ makes people ‘hungry’! This patterning with out deep understanding of how things work in evolutionary systems is what hurting the Recruitment space. A lot of people, especially non-technical folks in recruitment, have vested their blind faith in Machine Learning or Mimicking because they find it much easier (also the comfort that others are also using it) than understanding what human thinking should get into modeling AI for recruitment.

It is avowed goal at Turbohire to stay away from Machine Learning, more important to us is whether we are deeply connected and understand how people take decisions in recruitment.

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