Education/Research

Future Digital Economy Is Led by AI… But Human Is Still the One Steering

  • In the era of abundant data, as quality becomes more important than quantity, the spotlight is on capabilities to select and analyze.
  • The demand for artificial intelligence (AI) has increased, but it requires human intervention to use the technology.
  • Reasonable and optimized information will lead to the digitization of the future industry and a digital economy.

Globally, both digitalization and electrification are spreading at a fast pace. The number of digitally connected devices is ten times more than the human population and as the result, the amount of generated data and electricity consumption have grown tremendously.

The demand for artificial intelligence (AI) has been steadily increasing over the past few years. However, as the demand spiked up nearly 6 times more than usual during the recent five years, it became a hot issue in the industry.

This trend comes from growing demands on technology to obtain relevant information out of numerous data.  The era which is led by technology and data now is called the digital economy.

The advancement of AI technology is now more and more accelerated. It is estimated that the global consumption of the recognition system and AI will increase sixfold between 2017 and 2022.

Every day, a countless number of products and services are being developed and data is being generated, but only about 10% of them are used for analysis using AI. In other words, this field has very high potentials for growth in the years to come.

In this era the spotlight is on capabilities to select and analyze. Increased demand for artificial intelligence optimized information leads to a digital economy.

We often think that artificial intelligence will replace humans once it is fully implemented in the industry. However, AI cannot replace humans completely. Because it is the people that manage the quality of data and use the data.

Thus, we need to put more trust in people-centered businesses, and we should research to revitalize the business. I have started research on AI about 30 years ago. At that time, there were two major problems, computer capacity and the usability of data. In the last 30 years, the processing ability of computers and the usability of data have improved dramatically, leading to the rapid advancement of technology. However, the amount of work required to rationalize the data and extract the best data for the operation has not changed.

Regardless of the application (app), the quality of the result solely depends on the quality and composition of the data entered. The amount of data does not affect the quality of the outcome. Rather, the quality of data largely depends on the accuracy of the data and the level of utilization. This is what will be accomplished by humans and technology. Increasing the precision that extracts high-quality information and applying the information in real settings should be done by humans, and this is what the key to AI is.

Also, the smooth implementation of AI in industries requires the adoption of stable and specialized systems that can be incorporated into every level of a corporation. Not only data experts but also members in the field must be able to trust and utilize the significant impact of the data. To do so, we must set up an efficient process and usage by using technologies and solutions.

Over the past few years, we stood at the center of innovation and committed to cooperate and grow together by supporting business incubators, investing in ventures, and utilizing abundant partner networks. This was to advance AI-related apps and ultimately have them adopted in industries so that we can be a pillar of the digital economy. It was one of the ways to support sustainable development as well.

The digital economy not only provides efficiency and convenience but also reduces capital investment as well as operation and maintenance costs. If the reliability of AI reaches 50% or more, the cost of unexpected shutdown can be lowered by reducing sudden shutdowns of facilities.

To successfully deploy AI in the industry, we should consider expanding the ecosystem in the future by using open architecture, prevent data distribution and disconnection by integrating industrial and engineering software, increase the quality of domain expertise, and make attempts to expand efficiently after going through tests for some.

Of course, the most important factor is that everything should be focused on humans. You must remember that the key to success comes from enabling people to use data better and to make better use of AI-powered apps.

COVID-19 changed many things dramatically, but it didn’t change the real priorities. It just pushed us to deal with difficult challenges and requested us to make fast and bold decisions.

It made us recognize digitalization as an essential factor, not an optional one, to a company’s survival, and the companies that respond to this change promptly have gained a considerable competitive edge. In the future, various factors including artificial intelligence will further accelerate the digitalization of our industry. We hope to equip ourselves with the ability to restore and recover in operation by accepting and developing the digital economy that has already started to overcome other crises in the future for sustainable business.

This article was originally published in Maeil Economic Daily


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