Research motivations

1. Research motivations

  Our Residential Environmental Design Department addresses both the design and research areas, and that is one of the chief characteristics. But it seems that the disconnection between the architectural design practitioner and the architectural planning researcher remains unsolved. For example, in the architectural planning phase, the designer would consider various aspects, such as the relationship with the surroundings, the behavior and psychology of the users, assuming the realistic situations after completion. To make an attractive proposal, a great deal of passion and effort will be made at the design phase, but when the building is completed, the comparable energy will not be put into verifying the initial assumption, discovering or reflecting knowledges and laws derived from operational phase. As researchers, on the other hand, tend to place more importance on logical consistency, suffered from side effects of specialization and subdivision in the research area and researcher’s performance evaluation system, sometimes applicability and usefulness are not emphasized.
  How can we resolve the disconnection between them? The question arose while getting the opportunity to experience both design and research fields. Actually, in the field of design methodology, it was a basic theme from more than half a century ago, but the concept of cross-sectoral research against it became one of my goals.

2. Design and natural science

  Both design and the natural sciences are dealt in university lectures, but their characteristics are quite different. The natural sciences are concerned with "how things are" as the logic expands deductively, such as A is B. While design is concerned with "how things ought to be", and it depends on an inductive or abductive reasoning, such as A should be B. Thus, the natural sciences aim to clarify the true essence of nature independently of human intention and emotion, while design aims to devise artifacts to achieve a certain purpose^[1].
  To put it most simply, design is regarded as "combining" and natural science as "dividing". "Combining (tsu-ku-ru: Japanese)" has the origin of "tsu-ku (com-bine: make two into one)" and it represents composition by linking something with something, "Separating (wa-ke-ru)" is to break "apart (wa-ru)" something into smaller elements. Natural science discovers laws and theorems by decomposing complex phenomena into elements and attempts to approach the truth^[2]. "Separating" is synonymous with "solving (wa-ka-ru or to-ke-ru: unbind)". Design, on the other hand, synthesize and compose artifacts for a certain purpose from various elements, knowledge and techniques. Natural science has revealed that organic matter is made of carbon, hydrogen, oxygen, etc. When designing substances, however, made of carbon, hydrogen and oxygen, an infinite alternative would come up. In natural science the correct results are the same regardless of who does it, while in design totally different products are evaluated as correct or beautiful dependent on designer, times, culture, trends, techniques, etc. (Evaluation may be reversed thereafter.) Therefore, both are considered to be in an opposite relationship.
  Both are basically heterogeneous, however, as every artifact is made from nature and exists under the natural laws, they are inseparable from each other. A discontinuity arises within the university or society, which relates both sides, and having a dilemma is due to the heterogeneity and homogeneity of them. For example, the Architectural Institute of Japan addresses a vast academic field at present, but its predecessor, the House Building Institute, was a place for practical knowledge, and its core theme was not science but design. The home economics, which is the origin of our Human Life Science, was the same. Design, however, is more difficult to formulate and lacks strictness and objectivity compared to the natural science, which can be concluded as "A is B instead of A should be B", so one day the design was no longer a major research subject at university, and more academic natural science has come to dominate it. As a result, in engineering departments, physics, chemistry and mathematics are almost at the center of research, and design-based academics such as architecture and home economics tend to be regarded as a minor research fields. Meanwhile, in industry and society, the lack of professional education at the university, in other words, the divergence between scientific knowledge which is the center of research and expert knowledge that the practitioner should have is concerned. In response to this situation various countermeasures were invented, and among others Schön's^[3] concept of "reflective practitioner" has influenced extensively, including modern experts, researchers in the field of design, higher education and so on. Currently, application of professional knowledge and fragmented scientific knowledge captured by conventional knowledge framework is inadequate, as social problems are highly complex and complex, thus under the dialogue with the situation, the problem-solving methodology using cross-sectoral knowledge inductively and abductively is suggested through the professional model of reflective practitioner.




3. Scientific method

  Natural science and design have different properties, but the way of approach to problems is in common. The general process of scientific methods that measures phenomena by experiments and observations, analyzes data, finds laws based on cross-sectoral knowledge, predicts unknown phenomena by applying laws, which is similar to a "reflective practitioner" who grasps the situation, gains insight through his own experience and the reflection on circumstances, and attempts new practice. Even in natural science, discovery of unknown law, the solution process of ill-defined problems^[4], is done by design-like, and inductive, especially abductive inference plays an important role^[5]. If how to reach the solution is not known immediately, actions and reflections are necessary, and the process of problem solving and the methodology (method of choosing methods) themselves become central issues.

4. Human behavior in built environment

  Every artifact, including the built environment, is designed to serve people. In the design of the built environment, it is fundamental purpose that human behavior, body, cognition, psychology become a healthier and preferable state. For research on human subjects, acquisition of data that is guaranteed to be rigorous, accurate and objective like physicochemical experiments is often technically and morally difficult, and for example, in the field of architectural planning, methods of applying statistical analysis to observation, questionnaire, interview data are often used. As the development of microscopes and analytical instruments has brought about the development of natural science, it is also important to work on measurement and analysis methods themselves.

5. Human, the weakest link

  At the built environment used by many and unspecified users, it is necessary to design a situation that is more desirable for more and vulnerable people, however, humans differ in personality and acquired character, they do not take the same action and do not have the same psychology even under the same circumstances. Meanwhile, it is also known that there are some kind of behaviors tend to be repeated over time and taken by many people in similar situations and environments^[6]. Although it cannot be expected to be rigorous like physics experiments, it is possible to conduct research based on scientific methods by devising measurement and analysis methods.
  In a survey to acquire a large number of people's behavior over a long period of time, it is necessary to process huge amount of data obtained, so-called big data. With the development of computer science and analytical methods, it has become possible to acquire and process big data, which was not easy in the past. Recent technological development in the information field is remarkable and leading among all industries. Various artifacts intervene in the built environment and continue to provide new value every day to our lives. The idea of IoT where all artifacts are connected to each other is prevalent, but it is as already pointed out that the last frontier of the ring is a human being (Human, the Weakest Link^[7]). It is also shown in the business model of AGFA (Apple, Google, Facebook, Amazon) which produce great value by acts, remarks, interests and biometric data on human beings connected to artifacts link.





6. Architecture: Oldest, largest, mostly parent artifact

  Architecture is the artifact that acts as the foundation of life, as old as human history, the largest scale, and we rely on the longest time every day, however, while cars and mobile phones evolve the ability to respond to human acts and words, architecture has little knowledge of whom, when, where, and what they are doing inside. As outdoor GPS widely spreads and bringing various added value, the value generated by sensing behaviors such as the position of a person inside the building is not small. And as data processing methods became more common in machine learning such as deep learning and innovation in computer science, the collected personal data themselves became valuable. Conversely, the situations where various human data is not acquired in the buildings of our daily life may be a loss of opportunity to extract value. As AI's ability is rapidly growing in areas where advanced intelligence is required such as chess and shogi, computers can learn new data continuously, gradually improve accuracy and quality of reasoning models^[8]. It is being automated in multiple fields to extract the hidden law behind which people cannot notice, even if they can see the situation. There, a new architectural artifact model could be expected. It supplements functions by continually sensing human behavior in the built environment without burden, finding knowledge by machine learning, improving efficiency or predicting problems. In architectural design, not only the static space design but also the artifacts system behaving in response to human behavior and dynamic environment is awaited, as it were upgrading to the next-generation artifact, kinetic architecture.

7. Behavior measurement in medical welfare facilities

  Currently, we are conducting a research^[9] aiming at establishing a methodology to improve the quality of life by measuring and encouraging the behavior of staff and users in medical welfare facilities. Concepts such as nudge in the field of economic behavior and gamification are the ideas that lead people to make a more rational decision by inducing action without specific compulsion or compensation. We are conducting the research by continuous analysis of behavior data of staff and users within nursing home in order to improve wellness by voluntarily leading desirable behavior by advice, guidance, praise, etc. and offer a system that enhances efficiency by learning resultant data and continues to complement functions.

1. ^ Herbert A. Simon: The Sciences of the Artificial, The MIT Press, 1996.
2. ^ René Descartes: A Discourse of a Method for the Well Guiding of Reason and the Discovery of Truth in the Sciences, Kindle, Amazon
3. ^ Donald A. Schön: Reflective Practitioner: How Professional Think in Action, Basic Books, 1983.
4. ^ Churchman, C. West: Wicked Problems, Management Science, 4, 1967.
5. ^ C. S. Peirce: Collected Papers of Charles Sanders Peirce 1935, Science and Philosophy 1958.
6. ^ Barker G. Roger: Ecological Psychology, Concepts and Methods for Studying the Environment of Human Behavior, Stanford University Press, 1968.
7. ^ Kanade Takeo, Matsui Toshihiro: Human, the Weakest Link, The Japanese Society for Artificial Intelligence, Vol.20 No.5, 2005.
8. ^ Daisuke Matsushita: Alternatives selection method by machine learning in architectural design problem, dissertation of Kyoto Univ., No. 10193, 2003.
9. ^ Daisuke Matsushita: Encouragement of wellness of nursing home users by Bluetooth Low Energy positioning, Japan Science and Technology Agency, 2018.12-2019.11.