- Dean Atsushi Shimojima
[Doctor of Philosophy]
Born in Akashi, Hyogo in 1962.
Doctor’s Degree in Philosophy at Indiana University in 1996.
Before serving as Professor of the Faculty of Culture and Information Science, Dr. Shimojima served as Postdoctoral Fellow at ATR Media Integration and Communication Laboratory, Associate Professor at Japan Advanced Institute of Science and Technology, and Associate Professor of the Faculty of Culture and Information Science.
Specialized in logic and cognitive science, he is principally engaged in the semantic approach to the cognitive functions of diagrammatic representations.
To learn culture is to learn human beings.
The most important thing to human beings is human beings, and for this reason we have highly evolved intelligence to understand other people's behavior and its motivations. AI defeated us with chess and Igo, but in the "game" of understanding human beings, AI is no match for us. The best expert to understand human beings is human beings, not AI. Even if the age of AI has arrived, the role of understanding human beings will still be played by ourselves. So, we need cherish and develop our natural talent for understanding human beings.
As the name of our department suggests, we provide a place where students learn culture. For us, culture means patterns of human behavior in general, everything about human behavior, so to learn culture is to learn human beings. The students of our department conduct cultural research to acquire in-depth knowledge of human behavioral patterns, and through this activity, they also acquire scientific methods to gain still newer knowledge of human beings.
Below, you will be introduced to the two methods adopted by our department for such learning.
Method 1Multi-view approach to understand human beings
In the fields of humanities and sociology, various perspectives and methods have been cultivated to understand human behavior. We call on these foundations to capture human beings not only from a single viewpoint but from multiple perspectives. Our curriculum has three areas of focus for this purpose. The field of behavioral data science incorporates a psychological point of view that focuses on the work of the human mind taken individually, as well as a sociological point of view that focuses on human behavior and consciousness as a group. The field of linguistic data science provides a linguistic perspective that focuses on language as the most distinctive capacity of human minds. We also have a field of cultural resources science that goes back in time to study human beings, relying on the records and products of human actions taken in the past. While taking lectures and exercises in these fields, students are freed from the fixed, one-sided view of humanity and acquire the ability and attitude to understand human beings from various angles.
Method 2Information processing and data analysis to understand human being
Our second method is to become friends with information processing and data-analysis technology. We have emphasized that the best expert to understand human beings is not AI but human beings themselves.
This however does not mean that we should keep distance from the techniques of information processing and data analysis techniques in our effort to understand human beings. Our ability to understand human beings is certainly superior, but not almighty. It may be good enough to understand the behavior of a limited number of close acquaintances, as family members and friends in personal life. But in order to accurately understand the behavior of a large number of unfamiliar others in more public settings, we need the support from knowledge and techniques of collecting, accumulating, and analyzing detailed data about such a large group of people. The fourth field in our department's curriculum, foundational data science, is designed to help students acquire this knowledge and techniques.
To future students
All of us are experts in understanding human beings. It has always been we, the human beings, who understand human beings and decide where human beings would want to go. It will continue to be that way in future, and it must be so. If you find our two methods promising and wish to contribute to the future society with the multi-faceted knowledge of humans drawing on sound skills of information processing and data analysis, you are by all means welcome to our department.