The Future of Hiring with Machine Learning Technology

Posted by Crystal Miller on Apr 14, 2016 4:48:00 PM
Crystal Miller

Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. The human brain is prized for its ability to recognize and learn from patterns of events. Understanding patterns and predicting an outcome has been utilized in many industries, and HR is not an exception.

Here’s why you need to get on the bandwagon with machine learning technology:

Understanding Patterns

Algorithms and computer programs have been created to analyze thousands of patterns and relationships to find the match between two variables. Machine learning technology attempts to mimic the way humans naturally make patterns and associations when presented with new information. For example, a hiring manager with just a few years of experience will be able to spot the “warning signs” of a bad hire. After years of observation, he or she has cataloged a repertoire of undesirable/unprofessional behaviors and is able to adapt this knowledge to a novel situation, even if that candidate exhibits behaviors that are totally new.

Making Data-Driven Decisions

Human experience and understanding of commonalities between certain behaviors provide a valuable insight as to the most favorable outcome for the strongest working relationship between a hiring manager and a future employee. Today, programmers, scientists, and researchers are hard at work on creating Artificial Intelligence that replicates the intuitive and intelligent decision of a hiring manager. Our own predictive culture-matching software extracts information from a candidate’s professional profile and makes an algorithmic prediction as to whether or not she will fit in with the company culture and will be able to  work well with the hiring manager.

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Providing High Level of Accuracy

Machine learning technology in the form of Artificial Intelligence can predict hiring decisions with high levels of accuracy. There are hundreds of factors that determine whether a candidate is good for a job or not. By assigning weights to these factors, and matching them to the requirements of a job, our algorithms are able to predict whether a candidate would be a good fit or a bad hire.

No Need for Expensive Infrastructure

Humans are biased and will assign more weight to less important factors while neglecting or negating the crucial factors such as culture and behavior. With machine learning technology there is no need to hire a slew of people to go over applications or employ additional, complicated (and often expensive) recruiting software. With our technology, you will be able to experience a higher rate of accuracy as well as reduced overhead costs.

Smart Planning

Data collection, pattern identification and generating results without delays associated with the human error can help you plan ahead as to how many applications you need to have on hand at all times while accurately estimating your candidate closing cycle. For hiring to be done in succession, (e.g., actively recruiting before the busy holiday months) while lowering overhead during the slower summer months, a longitudinal view is needed. Machine learning technology that integrates well with an agency’s business model and ATS systems allow business owners to take a longitudinal view of the coming hiring year.

Machine learning reduces the scramble for candidates and staff by being able to anticipate busy seasons or shifts in industry verticals. Although we are a few decades away from true Artificial Intelligence, machine learning software that exists today allows businesses to operate more efficiently by selecting candidates who would be the best fit for the given organization. 

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Topics: predictive analytics, hiring decisions, machine learning technology

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