The development and diffusion of science innovative technologies is indispensable for modern society. However, despite its benefits, the development of science and technology is not without various risks and social problems. So far as we are going to make societal decisions for the use of science and technologies with diverse social implications that encompass both risks and benefits, sometimes involving values implications, there is a need for mechanisms of decision making and management of the development and utilization of science and technology. Decisions can be different depending on environmental, institutional and cultural conditions. In addition, innovative policy instruments/ mechanisms to deal with rapidly changing science and technology, including regulatory measures, are required for implementing decisions. This course will deal with wide range of issues from local to global levels faced at the interface areas between science, technology and public policy from comparative perspective of Japan, the US and Europe. It offers key theoretical issues surrounding Science and Technology and provides students with the tools and frameworks, such as risk assessment/ management and transition management, to analyze them. This course invites students from both natural science backgrounds (i.e. the graduate school of engineering, new frontier science and so on) and social science backgrounds (graduate school of public policy, law and politics, and economics and public policy). We expect students to acquire interdisciplinary perspective in addition to their primary major, which is one of the critical skill in analyzing complex social technical issues posed by science and technology.

The development and diffusion of science innovative technologies is indispensable for modern society. However, despite its benefits, the development of science and technology is not without various risks and social problems. So far as we are going to make societal decisions for the use of science and technologies with diverse social implications that encompass both risks and benefits, sometimes involving values implications, there is a need for mechanisms of decision making and management of the development and utilization of science and technology. Decisions can be different depending on environmental, institutional and cultural conditions. In addition, innovative policy instruments/ mechanisms to deal with rapidly changing science and technology, including regulatory measures, are required for implementing decisions. This course will deal with wide range of issues from local to global levels faced at the interface areas between science, technology and public policy from comparative perspective of Japan, the US and Europe. It offers key theoretical issues surrounding Science and Technology and provides students with the tools and frameworks, such as risk assessment/ management and transition management, to analyze them. This course invites students from both natural science backgrounds (i.e. the graduate school of engineering, new frontier science and so on) and social science backgrounds (graduate school of public policy, law and politics, and economics and public policy). We expect students to acquire interdisciplinary perspective in addition to their primary major, which is one of the critical skill in analyzing complex social technical issues posed by science and technology.

【注意】この授業は開講日程の都合上、成績が所定の確認日より後に公開される見込みが高いので留意すること。特に2年生は本科目の成績が進学選択が可能となる条件に含まれない見込が高いので、履修にあたっては十分に注意すること。 教養学部後期課程（理系）・統合自然科学科の「統合生命科学コース」には、ライフサイエンス研究の若きトップランナーが集結し、生命科学のフロンティアを開拓しています。本ゼミの履修学生は、最先端の研究を展開している研究室に数名ずつ配属され、未解明の研究課題に実際に取り組んでもらいます。 研究の進め方は教員と相談して決めます。研究室によって曜限を指定する場合、指定しない場合、集中して行う場合があります。セメスターの最後に、履修者全員が参加して成果報告会を開催する予定です。 統合生命科学コースの特徴は、先端性と多様性である。准教授が独立した研究室を運営できるため、２６もの研究室がある。その研究テーマは極めて多様であり、分子生物学や細胞生物学、植物生理学といった理学的な基礎研究から、神経科学、内分泌学といった医科学的な研究、そして、創薬などを目指した薬学・農学・工学的な研究まで多岐にわたる。ノーベル生理学・医学賞を受けたオートファジー研究が駒場で開始されたという事実が象徴するように、流行にとらわれない独創性の高い研究が行われている。実験や理論などのアプローチ法も多彩である。若き教員が柔軟な発想で、先端的でチャレンジングな研究テーマを選び、熱心に学生を指導するのみでなく、教員自らが現場に立って実験をしている研究室も多い。 生命科学およびその関連・融合分野に興味があり、新しい分野を切り拓きたいという熱い想いを持つ学生を歓迎する。また、文系から理系への転向を考えている学生も受講できる。教科書で学ぶことの先にある生命科学の最先端を体験して欲しい。

Statistics and biometrics have emerged as crucial disciplines not only in agricultural sciences but also in various other fields. This significance is primarily attributed to three factors: Firstly, advancements in data measurement techniques have facilitated the collection of extensive and diverse biological and agronomic data that were previously unattainable. Secondly, the evolution of data science methodologies has enabled the integration and modeling of such collected data. Thirdly, the enhancement of computational capabilities has empowered the utilization of these methodologies. These advancements have rendered statistical and biometric methods indispensable for extracting insights from the vast and varied biological and agronomic datasets. Throughout this lecture series, a diverse array of biological and agronomic datasets will serve as illustrative examples to demonstrate various analytical methods. Delivered in a hands-on format, utilizing R, Python, and Matlab, the aim is to equip students with practical analysis skills. The initial portion of the course, spanning the first one-third, will focus primarily on techniques for summarizing, visualizing, and modeling relationships within multivariate datasets. In the subsequent one-third, students will delve into linear models, linear mixed models, local regression, and nonlinear models. Finally, in the last segment, students will explore image analysis, machine learning, and deep learning methods. While the course will cover a broad spectrum of methods, ranging from introductory to advanced levels, the emphasis will be on developing the capability to independently conduct analyses rather than on elaborating on the theoretical underpinnings of the methods.

This course covers principles and topics related to environmental sciences important for the development of the world. Global and local environmental issues related to climate change, agriculture and marine environment, will be introduced in the course.

Understand the nature of traffic flow including traffic congestion, traffic accident risk, and influence on general social activities including economy. Traffic engineering measures to alleviate negative impacts to the society should be systematically understood, including highway & street geometric design, traffic flow management and control, and utilization of emerging technologies including Intelligent Transport Systems. In this course, first, traffic flow fundamentals and queing theory will be provided following the General introduction. Highway capacity & road geometric design and safety, intersection design & control, and Intelligent Transport Systems and its applications are the contents to be studied in this course.

This course confronts philosophy's most profound questions about the human condition with data-driven insights from modern behavioral science. For millennia, philosophers have used reason and introspection to ask: What is knowledge? What does it mean to be moral? What is love and happiness? How to deal with human violence? How to be free? What is the self? In this class, we will place these classical debates about the human nature/condition in direct conversation with cognitive psychology, behavioral economics, and social/evolutionary psychology. We will explore how far science can answer philosophical questions. <<Learning Goals>> - Identify and articulate key classical philosophical problems in epistemology (knowledge), ethics (morality), and metaphysics (self, love, free will). - Explain core concepts from behavioral science, such as dual-process theory, cognitive biases, moral foundations theory, and affective forecasting, while reasoning about major philosophical inquiries. - Analyze how empirical findings from behavioral science challenge, support, or reframe traditional philosophical arguments. - Critically Evaluate the limits of both "armchair" philosophical reasoning and purely descriptive scientific data in addressing normative ("ought") questions. - Synthesize insights from both fields to develop more nuanced and empirically-grounded positions on complex human issues.

The goal of this course is to strengthen students’ ability to apply insights from the behavioral sciences to the design of policies and interventions that enhance the well-being of individuals and societies across diverse global contexts. We will pursue this goal by: - Introducing key origins and recent advances in behavioral science research, drawing from psychology and behavioral economics. - Critically examining the gaps that persist between research, evidence, and real-world practice. - Applying core behavioral science theories and strategies to the analysis and design of policies and interventions, with specific policy domains or institutional contexts. The applications we explore will span multiple domains, including public health, environment, management, education, business, politics, and international development. This class is not a comprehensive survey of behavioral economics or social psychology. Instead, it offers a curated selection of research and theories that are especially valuable for thinking about practical application.

The purpose of this lecture is to acquire the knowledge and application methods as users of statistical analysis and data science for modern industrial practice and process analysis. Students will develop a systematic problem-solving mindset, from understanding process data and identifying root causes, to building predictive models and verifying solutions through rigorous statistical reasoning. The course progresses from fundamental statistics to multi-variate methods and data science techniques with hand-on exercises within the fields of Chemical/Biochemical .

At the end of the course, the student should have familiarised with the key concepts informing epistemological and methodological debates in social science, such as hypothesis, theory, falsification, verification, covering law, causality, with particular consideration for positivistic paradigms and anti- or post-positivistic reactions. The student should be aware of the specific difficulties of social scientific disciplines in studying human societies arising from the problematic separation between the studied object and the studying subject, and the link between social science and the political dimension. He should familiarise with problems of social research design, starting from the specificities characterizing the various stages of social science research. The student should become aware of the functional classification of social science methods in qualitative and quantitative, familiarising with a number of techniques in both domains, while grasping that contemporary social research increasingly requires the application of different methods and interdisciplinary approaches, which also lead to the necessity of teamwork coordination. The course also aims at providing a large variety of examples where the concepts and principles described above find their application and didactic clarification. Those examples will focus in particular on the study of technology and its social impact. Finally, the student should become aware of the moral implications, limits and rules informing social science research, as well as of the role and importance of effective communication in the social sciences.