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The excellence of the "recommendation function" of video media and EC sites is tremendous. Since it displays your taste, you can save yourself the trouble of searching for videos and clothes, and support comfortable use of the Internet. [Photo] Although AI recommends interior coordination in Nitori, "displaying only your own tastes" may mean that you may lose the opportunity to come into contact with new values and stimuli. We asked Mr. Yoshiyuki Tamamiya, an associate professor of the Faculty of Education, Hakuoh University, who is familiar with social psychology, about the advantages and disadvantages of the recommendation function. ■ Is the recommendation function an evolution of "sales POP"? ――First of all, please tell us the story before the recommendation function was born. Yoshiyuki Tamamiya (Tamamiya): This is a recommendation function that is often seen in online services, but it can be said to be a development of POP sales promotion strategies such as "Today's Recommendation" and "Most Popular" that have been used in retail stores. Initially, it was used to draw the buyer's attention to what they wanted to sell from the perspective of the seller's profits. After that, online services such as EC sites and video media became widespread, and a recommendation function appeared. With the gradual evolution, the accuracy of "interactivity" that reflects not only the psychology and behavior of the seller but also the psychology and behavior of the buyer has increased. ――What kind of system does the recommendation function work on? Tamamiya: Since various behavior histories of users on the Internet can be grasped by Cokkie etc., we are introducing "things that sell" according to individual users. Currently, various recommendation engines (AI) are being developed to instantly match the huge amount of user data accumulated in a company with the attributes of users who visit a website, and present the most probable choice. In addition to simply making recommendations on the website, it is also becoming equipped with the ability to send reminders via email or SNS to users who have registered for the service. ――What are the advantages of the recommendation function? Tamamiya: In psychology and brain science, humans are considered to be "cognitive frugals" in nature. In other words, in our daily lives, we tend to "want to live as cospa as possible without using our heads as much as possible." This tendency is seen not only in humans but in all animals, but the background is that "the information that the brain can process at one time is limited". That's why we want to focus on what's important and not on what's relatively trivial. The recommendation function can be said to be a ship. For example, after watching one video on a video site, if you try to watch interesting videos one by one, it will be dark if you check each video with the number of stars. At such times, if the video media side recommends a video that is related to the video you were watching and is preferred by people who are close to your attributes, we will be happy to select and watch that video. ――It's true that you are saving time. Tamamiya: Yes. In the days when rental videos were the mainstream, I returned the videos I had watched and walked around the store looking for the next video to rent. However, it no longer requires such effort. This can be very beneficial in the sense that it has allowed us to save time and effort, and that much more time and effort to do other activities. ――What are the benefits other than saving time? Tamamiya: I once worked on research on digital textbooks, and from that experience, I feel that it is "very effective in the field of education." By using digital textbooks, self-contained learning is possible like traditional textbooks and reference books. Not only that, but digital textbooks make recommendations based on vast amounts of educational data about "what the student should learn next", which is expected to lead to more effective learning. ■ Can humans lose "diversity" with the recommendation function? --Are there any disadvantages of the recommendation function? Tamamiya: We are both cognitive frugal and "thinking reeds." From a brain science perspective, what sets us apart from other animals is the developed cerebrum. The cerebrum has a very important function when we think in a complicated way. Research has shown that "the cerebrum can maintain its function by continuing to use it." Relying on the convenient recommendation function and not thinking for yourself may not be very good for the cerebrum. ――It can be said that "saving time = loss of opportunity to think". Tamamiya: Also, from social psychology, it is possible to make various points about the recommendation function. We tend to prefer people who have the same hobbies and tastes as ourselves. It is thought that this is to avoid the unpleasant feeling "cognitive dissonance" caused by witnessing that the values that conflict with oneself are socially "correct". Therefore, you can join a fan club or connect with people who have the same hobby on SNS. The recommendation feature helps us avoid cognitive dissonance. This is because the recommendation function presents options based on the actions taken by a person similar to that person in the past, so you do not have to look at options that are different from your own hobbies and tastes. ――You keep away from unpleasant opinions and values. Tamamiya: That's right. It's great in the sense that you don't feel uncomfortable, but on the flip side, the recommendation feature is actually losing a very valuable opportunity. “Diversity” is one of the modern keywords, but society is made up of people with different values. By interacting with people who have different values, you can discover new things and grow. However, if you rely too much on the recommendation function, you will always be in contact with things with the same hobbies and tastes, and your values will be unified. The political division that has become a problem all over the world in recent years is a perfect example of this. ■ Sometimes it's important to stay away from the recommendation function-sometimes it seems necessary to accept something that is uncomfortable. Tamamiya: Yes. Unexpected new discoveries are called "serendipity", and we researchers are conducting research with this serendipity in the corner of our head. By doing so, you may reach a previously unclear truth that is not an extension of your hypothesis. The recommendation feature is very useful and useful, but sometimes you may come across something unexpected and wonderful by voluntarily collecting information and making choices. ――How do you expect the recommendation function to evolve in the future? Tamamiya: It may be a trade-off with administrative regulations, but it is conceivable to build a database that transcends territory. For example, by integrating the purchase history data of EC sites with mobile / transportation data such as mobile base stations and Suica, it may be possible to create more complicated but effective recommendations. In addition, it is expected that the processing speed of the recommendation engine (AI) will increase dramatically due to the generalization of quantum computers, and recommendations based on more advanced algorithms that were not possible until now will be presented instantly. ..
Yuki Mochizuki
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