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The 2006 Kyoto Prize
2006
11 /11 Sat
Place：Kyoto International Conference Center
The 2006 Kyoto Prize Kyoto Prize Laureates
Lecture topics
The More We Learn
Abstract of the lecture
"If you understand everything," says an old Japanese proverb, "you must be misinformed." This is a lesson a good scientist must never forget. True, we have decoded DNA, mapped the human genome, and even made some diseases disappear from the face of the earth. In my own limited area of expertise, the FACS instruments we developed have opened the way to stem cell transplantation, to curing leukemia and to unraveling many other secrets of the single cell. Yet, even as we think we know so much, a young scientist in my laboratory has just discovered an entirely new kind of immune cell, different from all those we have known before. When I was a young student blowing things up with my chemistry set or learning the mysteries of corn seeds and fruit flies at Brooklyn College, I might have indulged the fantasy that science would, in time, lead us to understand everything. But now I hope I know better. As our knowledge expands and as we develop new technologies that we cannot now imagine, our students and their students will always find more questions than they can answer. Our existential pursuit will never end. This is the joy and the strength of science, which we must once again defend against the irrational attacks of religious zealots who think they already know the ultimate Truth.
Lecture topics
The Use of Mathematics for Deciphering the Movement of an Object: A Historical Review of the Introduction of AIC
Abstract of the lecture
1. Introduction From my early childhood, I loved to examine tools and toys with moving parts to see how they worked. I ended up studying statistical mathematics, which is directly related to understanding the movements of objects, and continued scrutinizing the existing methodologies. 2. Mathematics of prediction In order to handle problems under the circumstance where the outcome is unknown, we attempt to predict the outcome to determine what measures should be taken. The mathematical expression of expectation in this case is probability. Trying to develop an interpretation of observational data with probabilistic view often suggests useful information for making a prediction. Often a method of statistical processing of observational data can be obtained by organizing this procedure mathematically. 3. Application to practical problems In the era of Japan's post-war reconstruction, I aspired to work on problems that were unique to Japan. I concentrated on the analysis and control of phenomena that fluctuated with time, and collaborating with researchers in related fields successfully developed models and methods for practical applications, such as the statistical control of the silk reeling process, analysis of the random vibrations of automobiles and the oscillations of ships, and the automatic control of cement kilns that showed random fluctuations, and also developed necessary software. The results were often an advance over what was known by overseas researchers at that time. 4. Clarification of the concept of likelihood The model used here expresses the probabilistic mechanism that generates the observational data and includes adjustable parameters. Using the observational data, we adjust the parameters to maximize the likelihood to determine the model. In this case, increasing the number of parameters results in an apparent better fit to the observational data, but adding unnecessary parameters raises the possibility of increasing the prediction errors. 5. The information criterion In the information criterion AIC (An Information Criterion), the evaluated score based on the likelihood is reduced by twice the number of parameters. This is a realization of the method of logic that discourages bringing in unnecessary elements. The definitional equation is simple and easy to apply. The information criterion can be viewed as a method to measure the closeness of a model to the hypothetical truth (true structure), and allows the comparison of differently structured models. This characteristic encouraged the development of new models and the field of application of the information criterion has been expanding continuously.
Lecture topics
One Life, One Thread, and One Piece of Cloth: The Work of Issey Miyake
Abstract of the lecture
I have always lived by the motto, "don't look back." I live in the present and look to the future. I was born in Hiroshima and experienced the atomic bomb; I have worked to transform all that experience into an energy and joy whose goal is only to celebrate life. I learned from many people: from my mother, above all, who told me to go forward without fear and with courage; from the dear art teacher at my elementary school, who first introduced me to the joy of creativity; and from the many great mentors whom I have had the great fortune to know and by whom I have been influenced throughout my career; by many good friends. I have also experienced a series of events, each of which has been a source of a major turning point in my life. I believe that my work and the person I am today are the products of each experience and of the guidance of all those whom I have met along the way. In my speech at the Kyoto Prize Commemorative Lecture, I plan to trace the many unforgettable encounters that, like warp threads, have woven the weft threads of my work. I will begin with "One Piece of Cloth", a concept I arrived at early on, after having searched for a link between the Eastern and Western cultures, and also discuss my approach to tradition and innovation. This touchstone of A Piece of Cloth has lead to many experiments and evolutionary phases in my work, which has often changed dramatically every eight to ten years. Finally, I will talk about my new work and the next project upon which I am embarking. Through this series of threads, the different fibers of my life's work, I hope to be able to convey the joy I have always had from the simple act of making things.
