It has been nearly half a century since I first entered the world of research. During that time, I have witnessed several major changes in the way research is conducted while working on research and development in the fields of systems and information, as well as in the fields of social and business.

The first thing that surprised me was that it became possible to update a computer's operating system online. This was around the time the Internet began to take hold in the mid-1980s. The hardware in question was a LISP machine, the most cutting-edge AI-dedicated machine at the time, and it was around this time that automatic software updates, which are commonplace today, began. The second thing that impressed me was when, at an international conference in Europe in the early 1990s, an email service was provided over a row of expensive workstations. One of the Japanese participants downloaded a Japanese language processing function onto one of the workstations, making it possible to exchange emails in Japanese. This was the first time I truly felt that we were immigrants to Earth.

The third environmental change was just before the 21st century, when web browsers became widespread and Google search engines became available to everyone. And today, as we all know, the barrier between foreign languages and Japanese is gradually disappearing. However, the biggest change I have experienced so far is the change that has occurred in the past year. Yes, in the research field related to us, the sudden spread of generative AI including Chat-GPT has had an enormous impact. It seems that the research methodology itself has changed completely.

Just as the spread of the internet transformed business, advancements in measurement technology changed physics and astronomy, and statistics and big data altered quantitative research methods in economics and marketing, new technologies have always revolutionized our approach to research. Furthermore, generative AI has transformed our research world, including qualitative research areas, in the past year alone.

Of course, training generative AI requires enormous costs and data, and the output of generative AI often contains "lies" known as hallucination. However, students and researchers who have conducted a certain level of research in a particular field will not survive unless they can master cutting-edge technologies with a low barrier to entry, such as generative AI. This is because in cutting-edge research fields, a large volume of results are published at a much faster pace than humans can read.

Of course, beginners need to experience firsthand the kinds of falsehoods that can be found in the information generated by generative AI. Fortunately, our university was wise to publish guidelines for the use of generative AI in April 2023 and to actively promote its use. I hope that new initiatives will be undertaken in future research at CUC Research Institute. In compiling this paper, I naturally used Microsoft Copilot. It's a tool that enhances my abilities!