Deep Learning in Human Resources is Not Going Anywhere

January 14, 20203:41 pm1681 views
Deep Learning in Human Resources is Not Going Anywhere
Deep Learning in Human Resources is Not Going Anywhere

In the future, data science is predicted to be the default strategy among many HR teams. Many experts commented that the past few years is unarguably the year of data science where deep learning took the biggest part along with AI and machine learning.

What is deep learning? 

Deep learning is an area of automatic leaning in which deep neural networks are studied. It is the type of machine learning that trains a computer to perform human-like tasks. However, different from machine learning that focuses on the bigger picture, deep learning sets up basic about data and trains computer to learn on its own and solve its own problems by recognising patterns using many layers of processing. 

See also: The Trends of Machine Learning in Human Resources

Sas institute explained that deep learning is to replace traditional formulation and specification of the model with hierarchical characteristics, allowing the system to generalise well, adapt well, and continuously improve new data that arrives.  

The usage of deep learning in the HR world

According to Pedro Domingos, deep learning has helped human’s task in terms of vision and speech recognition like self-driving cars and virtual assistance in 2019. This year, deep learning will take up a higher stage such as cognitive ones like language understanding and commonsense reasoning. What does it mean for HR? 

When deep learning reaches the level of language understanding and commonsense reasoning, HR can predict better on how to improve human capital performance by data that is stored in the algorithm. For example, after sufficient training, deep learning algorithms can begin to make predictions or interpretations of very complex data. As a result, HR can get the following points: 

  • Image and video recognition, making a robust recruitment process by identifying and classifying the candidate’s based on objective data. 
  • Speech recognition and virtual respond. Deep learning algorithms can be designed to recognise and respond to human voice inputs. Thus, it can help respond to common questions asked by employees accordingly. 
  • Recommendation engines. From two above, the most significant advantage of deep learning is the recommendation engines. Combining big data and deep learning, HR can better identify learning pathways that might interest individual employees. It can also be used for other purposes such as wellbeing program recommendation. 

How to maximise your deep learning usage 

Maximise your talent-hiring strategy and retention methods. In a fine term, deep learning combined with existing data can solve crucial employees and business problems. Yet, your deep learning usage should be accompanied by some important tools to get the most effective results. Based on Bright Computing data, here is what you need to help your deep learning performs better. 

  • Use relevant and clean data to get the latest result. 
  • Consider the context to get specific results. 
  • Continuously revise your algorithm such as upgrading hardware and software to help deep learning perform at its best. 
  • Use the right tools. Software used to develop deep learning solutions continues to evolve rapidly, thus, make sure you choose the right tool that aligns with your purpose and goals. 

Read also: Why Should HR Care about Big data?