Machine Learning in Hr

Machine Learning In HROver the last ten years, there have been many talks about big data as well as machine learning in HR. Are they overhyped? Well, we are just looking at the tip of the iceberg. In the HR world, things used to be super easy. In earlier days, HR’s primary duties were recorded maintenance and payroll. Over time other functions such as employee training, uniformity, and well-being were added to their tasks. Later on, recruitment and skilled workforce selection were added to their duties. Today, Human Resource Management (HRM) is presuming a more critical role than ever before. These days, not just that they are responsible for all the tasks mentioned, but they are also responsible for motivating the employee, well-being, and workforce development as well. The HR groups have more data at their fingertips than ever before. They are actively attempting to align individual target with the corporate goals and objectives.

Furthermore, strategic HRM focuses on actions that differentiate the organization from its competitors and aims to make a long-term impact on the success of the organization. Data and decision-making based on data, is gradually becoming more crucial. In recent times, an organization not only have the traditional roles but they also expertise in areas such as data science, data visualization, and machine learning. So yes, the HR data age is just beginning. In the data-driven world era - where everything is being calculated and decided based on numbers, figures, and facts – it is impossible for humans to understand and entirely interpret it. That has resulted in the introduction of Machine Learning to study the improved analytics models. Industrial robots, human-made intelligence, and machine learning are developing gradually at a steady pace, and people are bothered about their jobs. This brings the question of utmost importance, will robots take over the human jobs rendering them useless or a symbiotic association between robots and humans is possible?

Speed, Cost, and Quality

The advent of improved robotics and enhanced AI has increased the speed, quality, and cost of available goods and services while becoming a part of many businesses. This has resulted in many companies operating with a few numbers of workers. They have been designed to understand more human cognitive functions and with great ability to perform with more human-like possibilities. Automation has reduced the number of employed workers, along with the cost, needed to produce per unit of goods, products, or services – which extensively increases the demand.

For instance; the adoption of an assembly line by Henry Ford reduced the cost of cars and prices, and in turn increasing the demand for them and the employees building them. It is believed that increasing productivity and lowering rates will raise workers’ wages.

Not Beneficial For All

Automation will not make everyone benefit from it, and some workers will be displaced, and others(technicians or engineers) will derive more profit out of it. Automation will increase a range of newer tasks; which the machines cannot perform. Some experts warn of a staggering lack of employment, while others believe that it will create unique job categories for displaced workers. It is expected that in specific areas machines will replace humans, wherein others they will accommodate each other. There are also people from the panel of an expert who says that automation will not affect human employment and they will also work in a friendly relationship in the future.

Usability of Machine Learning

A lot of factories and warehouses now make use of robots that are relatively mobile, versatile and not too costly like their previous generations. Baxter, a robot designed in the USA, can take care of various tasks like loading and packaging – and costs around $25,000. Not just manual works but white-collar jobs are widely expected to be at risk from automation too. Quill, another robot designed by Narrative Science, can crunch data and create reports in a highly streamlined method. IBM’s Watson computer is giving medical experts some challenge with its ability to sift through medical histories, symptoms, and the most recent research to deliver diagnoses and suggest possible treatments. However, it is still time for robots to enhance their diagnostic capabilities and empathy – so, for now, they are working together by helping the doctors make the faster diagnosis.

Humans Can Be Better Creative

Optimists are believed to be in favor of automation because they think it will free up humans from the tasks to spend more time towards creative and mindful activities. The touch of personal interaction; such as empathy for patients, critical financial advice, and personalized expertise, etc. will never get out of human hands to automated machines. Any repetitive process is likely to be automated, while anything that requires an extensive analytical level and better articulation will stay with us. It is understood that humans will have to upgrade their ante of skills to outlive their posts by leveraging the technology in their favor.

Intelligent Technologies

There is potential for smart technologies to augment and boost our jobs rather than replace them. For instance; Bank tellers have successfully reduced their time-spend on money responsibilities and are now using the same to provide relationship-based operations to bank customers. We have to invest our time and money in gathering skills that cannot only save our jobs but also perform well against the robots. We humans will have to provide a range of options proving our utility to future-proof our jobs. We have to improve and add more strategic skills to hyper-specialize in our areas of expertise to get the better of the machines and work in an improved symbiotic environment. Businesses will need to get out of their comfort zones to build a perfect human-machine relationship for their longevity and more significant productivity.