Search result: Catalogue data in Spring Semester 2022
Science in Perspective  In “Science in Perspective”-courses students learn to reflect on ETH’s STEM subjects from the perspective of humanities, political and social sciences. Only the courses listed below will be recognized as "Science in Perspective" courses. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Type B: Reflection About Subject-Specific Methods and ContentsSubject-specific courses. Particularly relevant for students interested in those subjects. All these courses are also listed under the category “Typ A”, and every student can enroll in these courses. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0585-38L | Data Science in Techno-Socio-Economic Systems  Number of participants limited to 130. This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations. Particularly suitable for students of D-INFK, D-ITET, D-MAVT, D-MTEC, D-PHYS | W | 3 credits | 2V | D. Helbing, N. Antulov-Fantulin, V. Vasiliauskaite | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces how techno-socio-economic systems in our complex society can be better understood with techniques and tools of data science. Students shall learn how the fundamentals of data science are used to give insights into the research of complexity science, computational social science, economics, finance, and others. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The goal of this course is to qualify students with knowledge on data science to better understand techno-socio-economic systems in our complex societies. This course aims to make students capable of applying the most appropriate and effective techniques of data science under different application scenarios. The course aims to engage students in exciting state-of-the-art scientific tools, methods and techniques of data science. In particular, lectures will be divided into research talks and tutorials. The course shall increase the awareness level of students of the importance of interdisciplinary research. Finally, students have the opportunity to develop their own data science skills based on a data challenge task, they have to solve, deliver and present at the end of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Will be provided on a separate course webpage. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Slides will be provided. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Grus, Joel. "Data Science from Scratch: First Principles with Python". O'Reilly Media, 2019. https://dl.acm.org/doi/10.5555/2904392 "A high-bias, low-variance introduction to machine learning for physicists" https://www.sciencedirect.com/science/article/pii/S0370157319300766 Applications to Techno-Socio-Economic Systems: "The hidden geometry of complex, network-driven contagion phenomena" (relevant for modeling pandemic spread) https://science.sciencemag.org/content/342/6164/1337 "A network framework of cultural history" https://science.sciencemag.org/content/345/6196/558 "Science of science" https://science.sciencemag.org/content/359/6379/eaao0185.abstract "Generalized network dismantling" https://www.pnas.org/content/116/14/6554 Further literature will be recommended in the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Good programming skills and a good understanding of probability & statistics and calculus are expected. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0740-00L | Big Data, Law, and Policy Does not take place this semester. Number of participants limited to 35. | W | 3 credits | 2S | S. Bechtold | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces students to societal perspectives on the big data revolution. Discussing important contributions from machine learning and data science, the course explores their legal, economic, ethical, and political implications in the past, present, and future. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course is intended both for students of machine learning and data science who want to reflect on the societal implications of their field, and for students from other disciplines who want to explore the societal impact of data sciences. The course will first discuss some of the methodological foundations of machine learning, followed by a discussion of research papers and real-world applications where big data and societal values may clash. Potential topics include the implications of big data for privacy, liability, insurance, health systems, voting, and democratic institutions, as well as the use of predictive algorithms for price discrimination and the criminal justice system. Guest speakers, weekly readings and reaction papers ensure a lively debate among participants from various backgrounds. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0732-03L | Intellectual Property: An Introduction Number of participants limited to 150 Particularly suitable for students of D-ARCH, D-BIOL, D-CHAB, D-INFK, D-ITET, D-MAVT, D- MATL, D-MTEC. | W | 2 credits | 2V | R. Zingg | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course introduces students to the basics of the intellectual property system and of innovation policy. Areas covered include patent, copyright, trademark, design, know-how protection, open source, and technology transfer. The course looks at Swiss, European, U.S. and international law and uses examples from a broad range of technologies. Insights can be used in academia, industry or start-ups. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Intellectual property issues become more and more important in our society. In order to prepare students for their future challenges in research, industry or start-ups, this course introduces them to the foundations of the intellectual property system. The course covers patent, copyright, trademark, design, know-how protection, open source, and technology transfer law. It explains links to contract, antitrust, Internet, privacy and communications law where appropriate. While the introduction to these areas of the law is designed at a general level, examples and case studies come from various jurisdictions, including Switzerland, the European Union, the United States, and international law. In addition, the course introduces students to the fundamentals of innovation policy. After exposing students to the economics of intellectual property protection, the course asks questions such as: Why do states grant property rights in inventions? Has the protection of intellectual property gone too far? How do advances in biotechnology and the Internet affect the intellectual property system? What is the relationship between open source, open access and intellectual property? What alternatives to intellectual property protection exist? Knowing how the intellectual property system works and what kind of protection is available is useful for all students who are interested in working in academia, industry or in starting their own company. Exposing students to the advantages and disadvantages of the intellectual property system enables them to participate in the current policy discussions on intellectual property, innovation and technology law. The course will include practical examples and case studies as well as guest speakers from industry and private practice. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0727-01L | Telecommunications Law Particularly suitable for students of D-INFK, D-ITET | W | 2 credits | 2V | C. von Zedtwitz | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction to the basics of Telecommunications Law for non-lawyers. The course deals with the legal regulations and principles that apply to telecom network operators and telecom service providers (fixed-line and mobile phone). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | By analyzing the most relevant legal provisions for a telecom provider in Switzerland students will learn about the main concepts of Swiss law. No previous legal courses required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | 1. History of Swiss Telecommunications Law 2. Regulation of network access (essential facility doctrine, types of access) 3. Universal Service 4. Phone service contracts (fixed line and mobile phone service) 5. Mobil communication radiation regulation 6. Telecommunication secrecy 7. SPAM-Avoidance | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The powerpoint slides presented in the course will be made availabe online. In addition, links to relevant legal decisions and regulations will be accessible on the course website. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | No mandatory readings. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Short written exam at the end of the semester (scope and materials to be defined during the course). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0739-01L | Natural Language Processing for Law and Social Science Particularly suitable for students of D-INFK, D-ITET, D-MTEC | W | 3 credits | 2V | E. Ash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course explores the application of natural language processing techniques to texts in law, politics, and the news media. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will be introduced to a broad array of tools in natural language processing (NLP). They will learn to evaluate and apply NLP tools to a variety of problems. The applications will focus on social-science contexts, including law, politics, and the news media. Topics include text classification, topic modeling, transformers, model explanation, and bias in language. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | NLP technologies have the potential to assist judges and other decision-makers by making tasks more efficient and consistent. On the other hand, language choices could be biased toward some groups, and automated systems could entrench those biases. We will explore the use of NLP for social science research, not just in the law but also in politics, the economy, and culture. We will explore, critique, and integrate the emerging set of tools for debiasing language models and think carefully about how notions of fairness should be applied in this domain. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Some programming experience in Python is required, and some experience with NLP is highly recommended. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0739-02L | Natural Language Processing for Law and Social Science (Course Project) This is the optional course project for "Natural Language Processing for Law and Social Science". Please register only if attending the lecture course or with consent of the instructor. Some programming experience in Python is required, and some experience with text mining is highly recommended. | W | 2 credits | 2V | E. Ash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This is the companion course for extra credit for a course project, for the course "Natural Language Processing for Law and Social Science". | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will be introduced to a broad array of tools in natural language processing (NLP). They will learn to evaluate and apply NLP tools to a variety of problems. The applications will focus on social-science contexts, including law, politics, and the news media. Topics include text classification, topic modeling, transformers, model explanation, and bias in language. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0602-00L | Shaping a DCent.Society: Assessing Societal Implications of Bitcoin, Blockchains & Smart Contracts | W | 3 credits | 2V | M. M. Dapp | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course investigates the potential long-term implications of distributed ledger technology on our societies. Students critically reflect the economic, political, ecological, and ethical implications of the Bitcoin cryptocurrency and the Ethereum smart contract engine (incl. DeFi) by exploring connections to disciplines such as economics, political science, psychology, sociology, and philosophy. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Compare the paradigm shift from Web 2.0 to Web 3.0 Distinguish a broad range of Web 3.0 concepts Hypothesize about economic, political, ecological, and ethical implications of Bitcoin, Ethereum, and decentralized applications Integrate ethical and governance considerations into the design of cryptoeconomic systems Justify own opinions about societal implications of decentralizing society | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Imagine... what if Bitcoin, Ethereum, and related distributed ledger technology will be wildly successful and flourish long-term? Which parts of our economies and societies would they affect? Could we indeed redesign our societies towards more sustainable action, more democratic governance, and more equitable finance by envisioning new ways of organizing, coordinating, and acting collectively? Or is this all make-belief because, after all, the Internet also under-delivered in important aspects of its huge promises? How can we critically reflect on the long-term implications of decentralizing technologies on our societies? Bitcoin is dividing the world. Due to its erratic price movements, some view Bitcoin as a useless Ponzi scheme at best and a complex, state-interfering “thing” at worst. Others, however herald it as the most important invention since the Internet or the printing press. In any case, the questions raised by Bitcoin are not only of academic interest: Is today’s fiat money system fair? Should people or the state create money? Is global anonymous transfer of digital value a good thing or not? Will Bitcoin supercharge renewable energy or do we need to switch it off to save the planet? Could it even bring peace by preventing states from financing wars or is this a preposterous claim? Ethereum, blockchain technology, smart contracts, and decentralized applications (dApps) seem to be less contentious and have caught the interest of companies and government for their specific technical characteristics. However, where is the evidence that decentralized technology is beneficial inside a hierarchical, “trusted” setting? Will unstoppable dApps empower us or create rigid machines steering our behavior? So, what to make of this extremely polarized debate and how to come to reasonable own conclusions when imagining the decentralization of society? The course aims to connect the cultural and historical preconditions to the long-term societal implications of Bitcoin, Ethereum, blockchains, smart contracts, and dApps. We will research and critically reflect economic, political, ecological and ethical consequences with the aim to formulate our own opinions about what is currently happening and what might happen in the future. To achieve this multi-disciplinary goal, we establish a common understanding of the technologies and inner workings of Bitcoin, Ethereum & Co. in the first part. We discuss selected aspects such as open source software, cryptography, cryptoeconomics, incentives, and complex systems. Why and how is Bitcoin a “trustless” system – or is it not? Why is an absolute scarce digital asset a big deal – or is it not? Why and how is Ethereum a “world computer” – or is it not? Why is an unstoppable system of dApps and decentralized autonomous organizations (DAOs) a big deal – or is it not? For a full picture, we will also examine other developments such as altcoins, Decentralized Finance (DeFi), stablecoins, and Central Bank Digital Currencies. This introduction will provide the technical background to move to the main part of the course, in which we go into depth on the potential societal implications of Bitcoin, Ethereum & Co. We will be covering various domains such as sound and fair money & its value, free trade & prosperity, incentive design & social behavior, sustainability & energy use, individual sovereignty & state control, democracy & geopolitics. We will thus be exploring connections between information technology and economics, political science, psychology, sociology, and philosophy. Throughout the course, students are regularly invited to debate in small interventions. They will work in teams to build their own critical analysis and arguments about a specific challenge/issue chosen from the course material. They will summarize their conclusions in a brief report and defend them in class in the final part of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture slides will be distributed on a weekly basis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Ammous, Saifedean. The Bitcoin Standard: The Decentralized Alternative to Central Banking. Hoboken, New Jersey: Wiley, 2018. Antonopoulos, Andreas M. Mastering Bitcoin: Programming the Open Blockchain. 2nd ed. O’Reilly, 2017. Antonopoulos, Andreas M., and Gavin Wood. Mastering Ethereum: Building Smart Contracts and Dapps. O’reilly Media, 2018. Dapp, Marcus M., Dirk Helbing, and Stefan Klauser, eds. Finance 4.0 - Towards a Socio-Ecological Finance System: A Participatory Framework to Promote Sustainability. SpringerBriefs in Applied Sciences and Technology. Cham: Springer International Publishing, 2021. https://doi.org/10.1007/978-3-030-71400-0. Dapp, Marcus M. “Toward a Sustainable Circular Economy Powered by Community-Based Incentive Systems.” In Business Transformation Through Blockchain, edited by Horst Treiblmaier and Roman Beck. Springer, 2019. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | For this ambitious and interactive course, we hope to attract students who are motivated by tackling large societal challenges with new decentralized approaches to human coordination. We think students with an open mind and interest in interdisciplinary aspects of their field of study will benefit most from this course. Programming experience is not strictly required but some basics about computer science may be helpful to see the potential societal implications of this new technology paradigm. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0125-65L | A Sampler of Histories and Philosophies of Mathematics Particularly suitable for students D-CHAB, D-INFK, D-ITET, D-MATH, D-PHYS | W | 3 credits | 2V | R. Wagner | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course will review several case studies from the ancient, medieval and modern history of mathematics. The case studies will be analyzed from various philosophical perspectives, while situating them in their historical and cultural contexts. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course aims are: 1. To introduce students to the historicity of mathematics 2. To make sense of mathematical practices that appear unreasonable from a contemporary point of view 3. To develop critical reflection concerning the nature of mathematical objects 4. To introduce various theoretical approaches to the philosophy and history of mathematics 5. To open the students' horizons to the plurality of mathematical cultures and practices | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0557-00L | Soccer Analytics Students should be comfortable with mathematical derivations and scripting for data analysis. | W | 3 credits | 2G | U. Brandes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Soccer analytics refers to the use of data in tactical decision-making, strategic planning, and fan engagement in the context of association football. This course is first and foremost about data, problems, and methods. They are discussed, however, with reference to the broader context of measurement and data science in sports and society. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students gain insight into the role of data science in professional football. They learn about attempts to capture aspects of the beautiful game in observable data to inform tactical, strategic, and communicative decision-making. By appreciating difficulties that arise even in activities with highly regulated interactions such as team sports, they reflect on the use of data science in the study of collective behavior. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The content is organized into lectures with time for reflective discussions and a practical part, in which small teams use free software tools to gain first-hand experience in working with sports data. The following is a tentative overview of course contents, with exemplary aspects listed for each topic. A major element for each of the analytic topics are various forms of visualization such as timelines, step plots, scatterplots, density maps, shot maps, and networks. 1. Introduction - history of measurement and analytics in sports - laws of the game: equipment, space, time, players - data: master, match, event, tracking; sources, availability, uses 2. Scores - competitions: tournaments, leagues - ranking teams: coefficients, latent strengths - predicting results: odds, statistics 3. Individual Actions - running: heatmaps, pitch control - passing: packing, line breaking, crosses - shooting: expected goals & co. 4. Match Phases - set pieces, penalties, free kicks, etc. - possession, location, organization 5. Collective Behavior - formations: spatial distributions, proximity networks - attacking: possession value, positional play, passing networks - defending: (counter-)pressure, marking networks - team composition: plus/minus, interactions 6. Environment - recruitment: player profiles, transfer market, agents, salaries - governance: clubs, leagues, associations, confederations - engagement: attendance, merchandise, social media - simulation: robocup, esports, fantasy football - betting market Fair warning: This is the first edition of the course and it may be adjusted depending on interest and feedback. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Credits are awarded for active participation and a group project. To get the most out of the project, basic knowledge of programming languages such as python or R is advisable. Whether the course is offered again will be decided at the end of the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0172-00L | Around 1936: The New Language of Science Number of participants limited to 40. As a research seminar, this course is mostly suitable for MA and PhD students. | W | 3 credits | 2S | J. L. Gastaldi | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The years around 1936 witnessed an intense intellectual production in all fields of knowledge. All those contributions had a common denominator: the reorganization of their fields around a formal conception of language, which changed our linguistic practices both in science and in everyday life. This seminar proposes a comparative reading of those texts, to understand that transformation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | During the seminar, students will be able to: ⁃ Acquire a broad interdisciplinary perspective on the history of formal languages and sciences ⁃ Obtain philosophical and historical tools for critically assessing the status language and sign systems in scientific practices - Become acquainted with concepts and methods in the history and philosophy of science ⁃ Develop a critical understanding of the notion of formal ⁃ Discuss the methodological capabilities of historical epistemology | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The years around 1936 (say, between 1934 and 1938) were the occasion of an intense and fertile intellectual production, opening new and long-lasting perspectives in practically all fields of knowledge, from mathematics and physics to linguistics and aesthetics, and even inaugurating or prefiguring new disciplines such as computability, complexity or information theory. Indeed, within those few years, famous seminal papers and works appeared by authors such as Einstein, Turing, Church, Gödel, Kolmogorov, Bourbaki, Gentzen, Tarski, Carnap, Shannon, Fisher, Hjelmslev, Schoenberg or Le Corbusier. Despite the diversity of fields of knowledge concerned by this intense production, all those contributions seem to have a common denominator. In essence, they all concern a reorganization of their respective fields around a new conception of language as being of a purely formal nature. In hindsight, it can be said this simultaneous intellectual effort ended up changing our conception and practice of language, of what it means to read and write, both in science and in everyday life. However, although simultaneous, those efforts were not necessarily convergent. Multiple tensions, incompatibilities and fragile alliances accompanied the emergence of orientations such as computability theory, complexity theory, structuralist mathematics, proof and model theory, logicism, information theory, structuralist linguistics or aesthetical formalism and constructivism. This seminar proposes, then, to perform a comparative reading of those original texts, to understand the nature of that transformation, the convergences and divergences between the different projects at stake, and how the singular way in which they have historically communicated still determines our contemporary practices and conceptions of language. Students will be required to choose one of the proposed texts corresponding to their area of competence, and present it to the other students in an accessible way. Presentations will be followed by a collective discussion, putting in perspective all the texts discussed so far. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | As a research seminar, this course is mostly suitable for MA and PhD students | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0125-81L | How Free Are We? Philosophical Theories on Freedom and Determinism Particularly suitable for students of D-BIOL, D-HEST, D-INFK, D-CHAB, D-HEST, D-PHYS | W | 3 credits | 2G | L. Wingert | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | We are praised for our achievements and blamed for our failures. It is presupposed that our doings are something that is up to us. "It is up to us" often expresses our attitude to treat us as free beings. But are we really free, hence responsible for our behavior? Or is our behaviour entrenched in conditions properly understood as deterministic ones? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Participants should learn to know and evaluate answers to the following questions: 1. How do determinists conceive of determinism and freedom? 2. What has freedom1 to be like, if we adult and healthy human beings should be responsible for our actions? 3. Are we justified in claiming that we do possess such a freedom1? 4. Is a scientific world view compatible with the ascription of freedom1 to us? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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