Generative AI: Approaching the issues hidden behind convenience and capability

The evolution of generative AI technology is remarkable, and generative AI-related products and services are being announced one after another. However, when it comes to using generative AI for business purposes, there are various disadvantages and problems. In this article, we will consider the problems of generative AI and countermeasures.

The rapid development of generative AI, including ChatGPT, which can be said to be the "first year of the generative AI era," is bringing revolutionary changes to various industries. Although the reasons for its introduction vary from company to company, such as improving work efficiency in some companies and generating new ideas in others, various implementation cases have been reported in domestic companies, and it is not difficult to imagine that generative AI will become even more indispensable for companies in the future as an important tool for generating corporate profits.

In addition, according to a survey by McKinsey & Company in the United States, the economic potential of generative AI is estimated to bring an economic effect of 2.6 to 4.4 trillion dollars per year, even if it is estimated only from the perspective of use cases, and the market is expected to continue to expand steadily. In Japan, the market is expected to grow by an average of 47.2% annually from 2023 to 2030, reaching 1.7774 trillion yen in 2030, a figure that is just under 15 times that of 2023.

There are many examples of generative AI-related stocks making a big splash in the stock market. For example, the stock price of SoundHound AI (SOUN) began to move in early February, and rose by about 4.6 times in less than a month to its high on February 27. SoundHound AI is a story from the US stock market, but there are also a number of AI-related stocks whose stock prices are rising sharply in the Japanese market. There is no doubt that stock prices will rise as the market expands.

It is not difficult to imagine that new generative AI-related products and services will be released one after another in the future. It is believed that in the future, generative AI will become multimodal, allowing users to seamlessly link multiple information and systems through generative AI without users being aware of the complexity of the system. For example, generative AI will become the UI, and it will be possible to select and utilize systems according to user input. In fact, it is becoming possible to use generative AI to design UIs and generate source code. A representative example is the AI ​​tool "Galileo AI" that instantly generates UIs. Since Galileo AI can be used immediately on a browser by anyone and can automatically generate UIs without coding, it has become a hot topic as it can significantly reduce the time required for UI production, which has been carried out using design software such as Figma and AdobeXD.

It is also expected that the use of AI agents will become more practical, and we will enter an era in which generative AI will move people and systems. Microsoft announced that its Copilot AI system can operate independently like a virtual employee, and OpenAI has released GPT-4 Omni, which can "see, hear, and speak," and the company's CEO Sam Altman said that AI agents have the greatest technical potential.

Though various companies are working to put AI agents to practical use in this way, it has also been pointed out that there are several challenges to overcome before AI agents can become widespread. For example, generative AI has a problem called "hallucination," which outputs erroneous information. When an AI agent uses generative AI, it may be influenced in some way to perform the wrong task or generate the wrong output. The fact that such AI agents do not always execute tasks correctly means that there is a high degree of uncertainty, making it a high hurdle to practical use.