There are goals to be achieved in each subject and class at school. Classes are held to achieve those goals. Classes have an evaluation process to see if the children understand the lesson and reach the learning progress goal. Classes have goals, content, methods, and evaluation flow. The teachers’ job was to support the children and improve their abilities. If generative AI were to take on some of these roles, it would be fun. The condition for teachers who interact with children is that they are in good physical, mental, and social health. In the educational field, it is required that teachers can demonstrate their abilities comfortably. However, as you know, Japanese teachers are exhausted. If a tireless “generative AI teacher” could be a helper, it would create a flow in which teachers can effectively demonstrate their abilities.
The introduction of generative AI into school classes has begun to be explored. With the emergence of various digital technologies, mechanisms for developing children’s talents are becoming possible. Companies are also actively entering the field. Konica Minolta has developed a generative AI system to support the learning of elementary and junior high school children and students. Generative AI, such as Chat GPT, learns information available on the Internet. These generative AIs run the risk of providing information that is not suitable for children’s education. Therefore, Konica Minolta has limited the learning data to curriculum guidelines, textbooks, and reference books so that the AI does not use inappropriate words in its answers. It analyzes the learning progress and displays messages tailored to each individual on a tablet. It is a support system that reports the students’ learning progress to teachers and allows them to use it to improve lessons at school.
Recently, it has been said that the idea gathering ability of generative AI is mediocre and excessive expectations should not be expected. Therefore, it seems that generative AI is not the core of intellectual work, but is often used to improve the efficiency of peripheral work. Generative AI has excellent translation and summarization speed. It seems that there is no reason not to use this. One company is taking advantage of this excellent ability. Until now, the person in charge read and analyzed the customer surveys themselves. By switching from humans to generative AI, the time required for analysis was reduced by 80%. In this workplace, generative AI reduced the burden on employees, allowing them to spend more time on planning. It seems to have become a more productive.
