SELECT PERSPECTIVES BLOG

What Is Machine Learning and How Can it Help Human Resources?

Posted by  Trevor McGlochlin

machine learning human resources

Machine learning was the hottest topic at the 2018 Society for Industrial Organizational Psychology (SIOP) annual conference. The human resources field has finally decided to follow other fields and make this topic a top priority. In an article written by Daniel Faggella for TechMergence, machine Learning is defined as "the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.”

The same article outlines basic concepts, models, challenges, and limitations for machine learning across fields. Most of us agree that AI and machine learning won't replace human judgment. However, how does machine learning change the field of HR? Why does HR need machine learning?

Though the answer might seem obvious, there are several reasons HR professionals are being proactive about understanding how machine learning can change, mold, and benefit their field. Sourcing, applicant tracking, and resume review, are some facets of HR that machine learning has already made more effective and efficient. Here are a few more ways in which AI and machine learning can support HR functions:

Chatbots Increase Efficiency and Consistency

One way that some HR departments have begun to integrate machine learning into their work is through chatbots. These bots can perform several HR tasks. There is potential to use these bots to schedule, answer basic questions about the application process or company, and conduct general communication. The application of chatbots in the HR world has already started to dramatically change the field in terms of efficiency and consistency in the initial stages of the hiring process.

Predictive Analytics Help Reduce Turnover

Analysis and reporting of HR data is limited by the availability and cost of resources, but with the help of machine learning this process can be nearly limitless. Machine learning can help to identify data trends and predict future performance and attrition. 

In a recent study, we employed predictive analytics using machine learning to look at a large organization using machine learning to analyze and predict turnover. They ended up finding that turnover was being caused more by certain drivers than others. This allows organization to focus more attention on those key drivers and lowering turnover. You can read more about the study in this summary: What Causes Employee Turnover and How to Reduce It.

Optimize the Employee Selection Process

If an organization typically conducts high-volume hiring, they have probably already adopted machine learning into their applicant tracking system and selection assessments. HR can benefit tremendously by using machine learning in the selection process, as it can help organizations understand who their applicants are, eliminate bias, get candidates through the hiring process faster, and gather feedback information to continuously improve their process.

Technology is and will continue to progress and evolve. The organizations that understand the importance that the role of advanced technology plays in their HR role will lead the way for their industry. This will allow the organizations to understand themselves better. Once they identify their weaknesses they can see where to allocate resources and fortify a prosperous future.

evaluating emerging technology trends in hiring tools

Tags:   pre-employment assessment, big data

Trevor McGlochlin

Trevor McGlochlin is a Research Analyst at Select International. He earned a Master of Science degree in Industrial and Organizational Psychology from Florida Institute of Technology. His areas of expertise include selection, employee turnover, organizational development, applied research, and statistical analyses. His analysis work is centered around validation, adverse impact, turnover analyses, assessment scoring, and other data analysis.

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