What is machine learning?

Machine learning refers to computational methods that utilise experience (past information) to improve performance or to make predictions. This program is further developed through the extraction of knowledge of data, where you have a question that you believe the answer is in the data.

Machine learning is progressing the digital world and affects nearly every industry. Human resource managers can utilise these programs to better identify potential candidates and conduct comprehensive performance reviews. To better understand the ways in which machine learning can enhance HR tasks, let’s first look at the concept of machine learning.

There are three main types of learning in machine learning:

Supervised learning

This is where you teach and train the machine using data that is well-labelled. The data will already be tagged with the correct answer.

Woman selecting data fields

Unsupervised learning

This is where the machine is trained using a data set that does not have any labels. The learning algorithm is never told what the data set represents.

Data concept

Reinforcement learning

This is similar to unsupervised learning, where the data is not labelled; however, when asked a question about the data, the outcome will be graded. An example of this is playing computer games. Once the machine plays hundreds of the same game, it will learn and develop a winning strategy.

Strategy concept

Smart emails through machine learning

Google uses machine learning in most of its products, one of which you are likely to use every day as an HR manager: Gmail.

In Gmail, machine learning is used to categorise your emails and filter through spam. This email program learns from the way that users react to certain types of content and identifies what is likely to be spam. Patterns are identified and used to distinguish between the types of content that users will want and don’t want.

The email program further uses machine learning by identifying key words in your email, such as ‘attachment.’ If you forget to add the attachment, but state that something is attached, the system will prompt you to make sure that something is attached before the email is sent.

Woman typing an email

Improving HR through machine learning

HR managers can utilise machine learning to streamline performance management duties, recruitment decisions and improve employee retention.

Machine learning is able to identify patterns for employees and predict employee outcomes for managers to review. Managers can see possible outcomes for potential employees and make recruitment decisions based on the data shown. The following are examples on how HR managers are able to use machine learning to benefit the industry.

Learning for recruitment

Online recruitment and job seeking platforms have streamlined the application process, increasing the number of applications companies receive. Searching through each resume individually is a long and difficult task that can be made easier through machine learning.

Establishing algorithms can help find the right candidate for a new position. Systems can separate candidates based on qualifications and other criteria set by the HR manager. Managers will then only receive the applicants that meet that criteria through the system.

Programs can also detect patterns and correlate a candidates’ past experiences and relevant skills to find the best fit with a company.

Candidate selection concept

Unbiased performance review

It can be extremely difficult for an HR manager to remain impartial during a performance review of an employee. To avoid unintentional bias, managers can set up software to evaluate performance data through algorithms.

Machine learning programs are also able to examine past performance trends of individuals, teams and departments to predict possible outcomes. This analysis gives HR managers and directors insight to make the necessary decisions to improve performance and morale of the company.

Business people interpreting data

Eliminating employee turnover

Studies show that 80% of employee turnover is due to bad hiring decisions. Programs can improve hiring efficiency by connecting the right candidate with the fit of the company.

Programs can improve the second most common reason for new employee turnover: a bad skills match. Systems can analyse criteria outlined on resumes and personality traits throughout the interview process. Comparing this data to successful employees within the company, helps HR managers match the best candidate with the role.

Job interview

Stay connected

Machine learning and artificial intelligence will continue to grow and affect a range of industries. From everyday tasks, such as emails to more complex roles, such as recruitment, machine learning can improve efficiency and accuracy.

Stay updated with PowerHouse Hub to see where machine learning and artificial intelligence will take us.