AI is a term that is used in literature and media. However, many people are unable to comprehend the true phenomenon.
Some people believe that AI is the realization of Terminator movies, while others think it’s the benign R2D2. There is a big difference between AI as it appears in movies and AI as it exists.
This article will discuss “real AI” used at Hitachi. It will also show how real AI has the potential to significantly influence HR shortly.
AI is a term that is used in literature and media. However, many people struggle to understand the true phenomenon. Some people think AI is the realization of Terminator or R2D2. However, the truth is that there is a vast difference between real AI and the AI seen in movies.
We will be explaining “real AI” at Hitachi. We will also demonstrate that “real AI,” as used at Hitachi, has the potential to influence HR shortly significantly.
Five Misconceptions About Artificial Intelligence
AI is not for those without a technical background
AI terminology such as “deep learning” or “neural network” is used to explain the topic. It gives the impression that people without technical knowledge will not be able to grasp basic concepts. However, AI is easy to understand and can be used by all functions, including HR professionals from any industry. HR leaders don’t have to worry about the technical aspects of AI. They can instead understand the essence of its purpose. This understanding will be crucial for HR.
Computers were the key tool that made this possible at a large scale. The institutionalization above was widely used. In addition, computers can quickly perform descriptive tasks by using rules. This rule-driven approach was well-suited for the 20th century, when roads, railways, telecommunications and other infrastructure expansions were common. These rules supported the growth of these expansions by ensuring that they controlled and closed systems. These rules-based systems still have many applications today.
Already, outcomes-direction has produced results. The outcome-direction method, developed by an expert group and applied to 14 industries (including banking, finance, retail, transportation, water, railways, business, human resources, and other settings), has already produced results. In these different domains, proofs of concepts have been successful in 57 cases. This technology is showing that it can revolutionize businesses. The key feature of this technology is its ability to improve outcomes in various fields without altering the underlying software that captured and recorded the data.
AI is a new technology or machine
AI is not a new technology or a machine. Instead, AI is the realization of the above “outcome direction” and the software tools that enable it to be realized.
The first step is to determine the numerical values that will indicate the improvement target and the range. It is called the outcome.
Second, gather past data about the outcome and determine what conditions or behaviours increase it. It is where we try to identify trends with the data. One example is “Taking this action [defined as anything that can be linked to the outcome] when talking business with this client increases order placement by 20%.” Many factors could influence the outcome. Then, determine the ultimate
weight of each factor’s effect. Finally, AIs can use the relative weightings of the factors to predict future outcomes depending on their prevalence to generate an evaluation formula.
The third step is to apply the formula derived from the weighted variables to your business or management decisions. In particular, prepare multiple options for the business or management decision and project the outcome based on the evaluation formula. It is how you evaluate the strength of an option. It allows flexibility to be made using past data. It is what AI does.
AI requires large amounts of data to be useful
AI is nothing if data isn’t used. There are many arguments for the importance of data volume. But, it is even more important to determine the problem we need to solve. It is crucial to identify the desired outcomes and define possible actions that will create them. It is something that only humans can do.
Additionally, required items include the target, outcome, actions and conditions. These three items together are what makes AI powerful.
Results of HR Research: Achieving happiness
The most important elements in problem sets are the outcomes. You will only get simple and non-valuable outcomes if you create a non-valuable outcome. If you give an unclear abstract outcome, it won’t be easy to achieve the desired outcome.
What should we choose as the most important outcome? Which outcome is best for society? Naturally, happiness is the best outcome. You can make happiness your goal by looking at many data points to help you achieve it.
Many people believe that employees’ happiness and well-being do not impact business. There have been many breakthroughs in measuring and analysing human behaviour, including wearable sensors. We can now quantify happiness by using an accelerometer sensor to gather data about employees during activity. It does not have to do with how much physical movement is visible. Therefore, it is possible to measure unconscious movement, which can help determine happiness.
AI Will Bring Us Closer
AI’s key characteristic is its ability to be borne out of diversity, both organizational and human. AI can identify the unique attributes of a company and help it stand out. Human assets are the foundation of companies. AI can use these assets to identify a company’s unique success characteristics. These traits lead to increased productivity for organizations. It is remarkable even if employees leave the company.
Many companies used to incorporate conventional automation, which created a gap in their market. After a time when technology was the advantage, AI offered something fundamentally new. Different management challenges and resources are required for different corporations. Different problem settings and data will result in an AI algorithm unique to each company. It will be a unique fingerprint for that company if you will. It allows for the development of individual strengths and weaknesses and innovation and achievement. It shows that people are the greatest asset to any company.
Another important characteristic of AI is its strikingly distinct approach to standardizing users using conventional computers. Applying AI data to HR Software could lead to the fear that people will control in an uncontrolled environment. Instead, AI can promote diversity within an organization and individual. It will mean that computer systems of the past and their control are no longer in control. AI will encourage diversity.
AI is Relevant Only for The Future, Not Now
AI is already being used to address various important HR and business challenges. William Gibson said, “The future is here.” It’s just not evenly spread yet.
Hitachi is currently undergoing a major organizational transformation. We have already begun using AI in HR. Hitachi is moving from being a company focused primarily on products to becoming a company that offers services to customers. Incorporating this transformation into employees’ lives and daily activities isn’t easy. Many jobs will need to be changed as we build this business.
The project I referred to was where Hitachi HR used AI. They had 600 employees working in many fields, and each employee was equipped with wearable labels sensors. We developed a management system that allows AI to send personalized smartphone messages based on collected data each day. It includes information about how employees can maximize each day and suggested interactions to increase their happiness and productivity.
Already, AI has been used to drive organizational transformation. These methods can use in a wide range of HR and organizational contexts such as education, selection-making and retention.
The future is now, and AI has already significantly impacted company success. But, action is the only way to make things happen. As a result, HR has the opportunity to make a difference in the workplace like never before.