Search result: Catalogue data in Autumn Semester 2024
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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| 851-0252-10L | Project in Behavioural Finance  Particularly suitable for students of D-MTEC. | W | 3 credits | 2S | S. Andraszewicz, C. Hölscher, A. C. Roberts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | In this seminar, students will study cognitive processes, behaviour and the underlying biological response to financial decisions. Research methods such as asset market experiments, lottery games, risk preference assessment, psychometrics, neuroimaging and psychophysiology of decision processes will be discussed. Financial bubbles and crashes will be the core interest. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course has four main goals: 1) To learn about the most important topics within Behavioural Finance 2) To learn to effectively select, review and present information using modern telecommunication tools 3) To practice working on group projects in hybrid working conditions (online + in-person) 4) To solve an applied behavioral finance business case stemming from an industry partner | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course does not contain mandatory reading. Instead, it offers suggested literature that provides guidance to the students who, prepare a presentation on core topics in behavioral finance. The point of this exercise is to critically select the most relevant information on a given topic and present to non-expert educated colleagues. At the same time, the audience learns about the key topics in behavioral finance. Every session involves a discussion moderated and supported by the lecturers. Throughout the semester, students work on solutions to real business cases stemming from a company partner. They can receive feedback and guidance from project leaders of the industry partner and from the academic supervisors. In the final meeting of the semester, students pitch solutions to their business cases. The course takes place entirely online. The objective is to prepare the students for the future work in online and hybrid arrangements. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Students from all domains of ETH and all levels of education are welcome in the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 363-0565-00L | Principles of Macroeconomics | W | 3 credits | 2V | J.‑E. Sturm, E. Baselgia | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course examines the behaviour of macroeconomic variables, such as gross domestic product, unemployment and inflation rates. It tries to answer questions like: How can we explain fluctuations of national economic activity? What can economic policy do against unemployment and inflation? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This lecture will introduce the fundamentals of macroeconomic theory and explain their relevance to every-day economic problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course helps you understand the world in which you live. There are many questions about the macroeconomy that might spark your curiosity. Why are living standards so meagre in many African countries? Why do some countries have high rates of inflation while others have stable prices? Why have some European countries adopted a common currency? These are just a few of the questions that this course will help you answer. Furthermore, this course will give you a better understanding of the potential and limits of economic policy. As a voter, you help choose the policies that guide the allocation of society's resources. When deciding which policies to support, you may find yourself asking various questions about economics. What are the burdens associated with alternative forms of taxation? What are the effects of free trade with other countries? How does the government budget deficit affect the economy? These and similar questions are always on the minds of policy makers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The course Moodle page contains announcements, course information and lecture slides. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The set-up of the course will closely follow the book of N. Gregory Mankiw and Mark P. Taylor (2023), Economics, Cengage Learning, 6th Edition. This book can also be used for the course '363-0503-00L Principles of Microeconomics' (Filippini). Besides this textbook, the slides, lecture notes and problem sets will cover the content of the lecture and the exam questions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 351-1109-00L | Introduction to Microeconomics GESS (Science in Perspective): This course is only for students enrolled in a Bachelor’s degree programme. Students enrolled in a Master’s degree programme may attend “Principles of Microeconomics” (LE 363-0503-00L) instead. Note for D-MAVT students: If you have already successfully completed “Principles of Microeconomics” (LE 363-0503-00L), then you will not be permitted to attend it again. | W | 3 credits | 2G | M. Wörter, M. Beck | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course introduces basic principles, problems and approaches of microeconomics. It describes economic decisions of households and firms, and their coordination through perfectly competitive markets. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students acquire a deeper understanding of basic microeconomic models. They acquire the ability to apply these models in the interpretation of real world economic contexts. Students acquire a reflective and contextual knowledge on how societies use scarce resources to produce goods and services and distribute them among themselves. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Market, budget constraint, preferences, utility function, utility maximisation, demand, technology, profit function, cost minimisation, cost functions, perfect competition, information and communication technologies | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Course material in e-learning environment https://moodle-app2.let.ethz.ch/auth/shibboleth/login.php | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Varian, Hal R. (2014), Intermediate Microeconomics, W.W. Norton | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course "Einführung in die Mikroökonomie“ (363-1109-00L) is intended for Bachelor students and LE 363-0503-00 "Principles of Microeconomics" for Master students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0742-00L | Contract Design I You can find all course materials and the most recent announcements on Moodle. Please log in to Moodle using your ETH or UZH credentials. It is NOT a legal drafting class focused on contractual language. Number of participants limited to 160. Max 80 ETHZ and 80 UZH Students | W | 3 credits | 2V | A. Stremitzer, A. Tacconelli | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Contract Design I is taught by Professor Stremitzer and aims to bridge the gap between economic contract theory, contract law, and the writing of real-world contracts. In this course, we take a systematic approach to contract design. This means we first analyze the economic environment in which a transaction takes place and then engineer contracts that achieve the desired outcome. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Contracts are agreements between parties to engage in transactions. A good contract creates value by giving parties the right incentives to meet their objectives. A good contract designer scrutinizes the economic situation in which parties find themselves and tailors the contract to the challenges at hand. To help you become sophisticated contract designers, we draw from insights for which more than half a dozen Nobel Prizes were awarded in the past two decades and transfer them to the art of writing real-world contracts. In other words, Contract Design will provide you with analytical tools to design contracts that help you be better lawyers, business leaders, and startup founders. We will cover topics such as moral hazard, adverse selection, elicitation mechanisms, relationship-specific investments, and relational contracting and apply the theoretical insights to real-life case studies ranging from purchases & sales of assets, oil & gas exploration, movie financing, production & distribution, construction & development, M&A deals, venture capital financing, to executive compensation and many other types of transactions. The course follows a flipped-classroom model: You will watch learning videos specifically produced for this course ahead of class. We will use class time to discuss real-world case studies. The videos will be made available before the lecture each week and need to be watched ahead of coming to class. Computer-graded quizzes at the beginning of each class will test students’ understanding of the concepts introduced in the videos. As the emphasis of this class is on class discussion, attendance is mandatory. Absent important reasons, you cannot miss class more than twice. The lectures will be recorded but only made available to those who miss lectures with excused absence. For ETH students: Your grade will consist of two parts: 1) You will take weekly computer-based quizzes during class time. Thus, it is important that you attend the lectures to be able to finish the quizzes and pass this course. 2) You compose short responses to take-home questions on case studies we assign and upload them ahead of class (Pass/Fail). Note that UZH and UNISG students enrolling in this course need to earn more ECTS for completing this course than ETH students (due to curricula reasons). This is why UZH and UNISG students must complete a written assignment in addition to the weekly quizzes and take-home questions. UZH students also have to complete an additional group project. UZH and UNISG students should check out the description of the class at their respective home institutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Handouts, prerecorded videos, slides, case studies, and other materials available on a dedicated webpage: contractdesign.org. Access to this webpage is free of charge for ETH students as ETH purchased a license for ETH students. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Attendance is mandatory. You are only allowed to miss two lectures unless there are special circumstances. Contract Design I is available to ETH students through the Science in Perspective (SiP) Program of D-GESS. This course is particularly suitable for students of D-ARCH, D-BAUG, D-CHAB, DMATH, D-MTEC, D-INFK, and D-MAVT. If you have any questions regarding the course, please write an email to the teaching assistants, Lucas Gericke (lucas.gericke@gess.ethz.ch) or Serge von Steiger (serge.vonsteiger@gess.ethz.ch). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0760-00L | Building a Robot Judge: Data Science for Decision-Making Does not take place this semester. Particularly suitable for students of D-INFK, D-ITET, D-MTEC. | W | 3 credits | 2V | E. Ash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course explores the automation of decisions in the legal system. We delve into the machine learning tools needed to predict judge decision-making and ask whether techniques in model explanation and algorithmic fairness are sufficient to address the potential risks. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course introduces students to the data science tools that may provide the first building blocks for a robot judge. While building a working robot judge might be far off in the future, some of the building blocks are already here, and we will put them to work. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Data science technologies have the potential to improve legal decisions by making them more efficient and consistent. On the other hand, there are serious risks that automated systems could replicate or amplify existing legal biases and rigidities. Given the stakes, these technologies force us to think carefully about notions of fairness and justice and how they should be applied. The focus is on legal prediction problems. Given the evidence and briefs in this case, how will a judge probably decide? How likely is a criminal defendant to commit another crime? How much additional revenue will this new tax law collect? Students will investigate and implement the relevant machine learning tools for making these types of predictions, including regression, classification, and deep neural networks models. We then use these predictions to better understand the operation of the legal system. Under what conditions do judges tend to make errors? Against which types of defendants do parole boards exhibit bias? Which jurisdictions have the most tax loopholes? Students will be introduced to emerging applied research in this vein. In a semester paper, students (individually or in groups) will conceive and implement an applied data-science research project. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0732-06L | Law & Tech | W | 3 credits | 2S | A. Stremitzer, J. Merane | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course introduces students to scientific and technological developments that require regulation or enable legal innovation. We focus particularly on the challenges to current law posed by prominent near-future technologies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course is designed for a wide range of ETH students as well as for law students who are keen to deepen their understanding of cutting-edge technology. It offers an overview of key legal areas important for technology regulation, complemented by guest lectures on emerging technological trends. In previous years, the course has featured esteemed speakers from various sectors, including industry leaders like Google, NGOs such as Digital Society Switzerland and The European Consumer Organization, regulatory bodies like the Swiss Competition Commission, and noted academics. The course is open to ETH students through the Science in Perspective program of the Department of Humanities, Social and Political Sciences. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The planned course outline is below. - Overview of Law and Technology - Fundamental Rights - AI & Discrimination - Landmark Big Tech Cases - Regulation of Digital Platforms & Content Moderation - Online Consumer Protection - Law and Tech Scholarship Series A number of recent regulations will be discussed, including the EU's AI Act, the Digital Services Act (DSA), and the Digital Markets Act (DMA), as well as emerging internet phenomena, like ChatGPT. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | You can find all course materials and the most recent announcements on Moodle. Please log in to Moodle using your ETH or UZH credentials. Then search for "Law & Tech (851-0732-06L, HS 2024)" and enroll. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0391-00L | Focus on the Human: Human-Centered Security and Privacy Lab The course is particularly suitable for all students who have already completed the course “Human-centered IT Security and Privacy” as some of the concepts introduced will practically be applied in this course. However, the relevant literature and necessary material will be provided to all students and basic concepts will be briefly summarized so that all interested students can participate. | W | 3 credits | 2S | V. Zimmermann, A. Toth | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | After an introduction on usable security as the intersection of computer science and psychology, students will form teams and work on exemplary security- or privacy-related research questions. The teams will develop and evaluate a concept for a human-centered solution. Through input sessions and milestone presentations the human perspective will be incorporated and reflected upon. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The course makes students experience an exemplary human-centered design process. They will learn about and practically apply human-centered design and evaluation methods that will allow them to view their solution from the human perspective, e.g., the user, developer or website owner perspective. By taking part in the evaluation of other teams, they will also take the user perspective themselves. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | At the beginning of the course, the students will receive an introduction to usable IT security and privacy and relevant concepts. Afterwards, a selection of current research questions from that area will be presented. The students form teams and select one of the proposed research questions. This question will accompany the students throughout the semester. They will design and evaluate a concept for a human-centered solution to that question. To be able to do so, they will receive input on human-centered design and evaluation tools. Their progress and the inclusion of the human perspective will be subject to feedback in milestone presentations. The students’ human-centered solution can take the form of a concept (e.g., a concept for a product or app), interface (e.g., a visual or tangible interface), or prototype (e.g., sketches, a click-dummy or a built prototype). The solution will then be subject to evaluations. The solutions will be user-tested by members of other teams that thereby take the perspective of a user themselves. In addition, the solutions will be analyzed from different stakeholders’ perspectives, such as developers or website owners. Finally, the students will reflect on potential changes that results from the evaluations and their consequences. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Literature Recommendations: Adams, A., & Sasse, M. A. (1999). Users are not the enemy. Communications of the ACM, 42(12), 40-46. Cranor, L. F., & Garfinkel, S. (2005). Security and usability: designing secure systems that people can use. " O'Reilly Media, Inc.". Diefenbach, S., & Hassenzahl, M. (2017). Psychologie in der nutzerzentrierten Produktgestaltung: Mensch-Technik-Interaktion-Erlebnis. Springer-Verlag. Diefenbach, S., & Hassenzahl, M. (2010). Handbuch zur Fun-ni Toolbox–User Experience Evaluation auf drei Ebenen. Dix, A., & Finlay, J., Abowd, G., Beale, R. (2004). Human-computer interaction. Pearson - PRENTICE HALL. Garfinkel, S., & Lipford, H. R. (2014). Usable security: History, themes, and challenges. Synthesis Lectures on Information Security, Privacy, and Trust, 5(2), 1-124. Nielsen, J. (1999). Designing web usability: The practice of simplicity. New Riders Publishing. Norman, D. (2013). The design of everyday things: Revised and expanded edition. Basic Books (AZ). Reuter, C. (2018). Sicherheitskritische Mensch-Computer-Interaktion. Wiesbaden: Springer Fachmedien Wiesbaden. Sarodnick, F., & Brau, H. (2006). Methoden der Usability Evaluation. Verlag Hans Huber. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is especially recommended after the related lecture "851-0390-00 G Human-Centered IT Security and Privacy". However, previous participation in the lecture is not a requirement and not necessary for succeeding in the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0763-00L | Supervised Research (Law, Economics, and Data Science) Does not take place this semester. | W | 3 credits | E. Ash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This is a supervised student project for 3 ECTS, supervised by the professorship of Elliott Ash (D-GESS). Students will adapt tools from econometrics and machine learning to questions in law, data science, and social science. Students must have some data science and/or statistics experience. Some programming experience in Python, Stata, or R is required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Apply tools from data science and social science to a new project, potentially in a group, to develop a paper or app. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Some programming experience in Python, Stata, or R is required. Some experience with data science or statistics is required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 851-0392-00L | Privacy Quantification and Usable Protection Mechanisms | W | 3 credits | 2S | N. Zufferey, V. Zimmermann | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students will gain an overview of the main privacy metrics that are used to evaluate privacy risks related to the use of a given technology. They will also be introduced to the concepts of privacy/utility balance and usable security. Practical exercises and reading of recently published scientific articles will be used to present practical cases of the theoretical tools presented in class. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | This course aims to provide the students with a global knowledge of the concepts related to privacy, and the methodology and tools to identify, analyze, and address threats while taking the user into account in the process. They will adopt a “privacy mindset”, thus enabling them to automatically take privacy into account, in a usable way, when designing or analyzing a system. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | First, the course will introduce the different definitions and approaches of privacy (e.g., privacy by control, privacy by design) as well as the ethical concerns and considerations related to information security and privacy research (e.g., responsible disclosure, full disclosure). Second, the students will be introduced to the different methods, properties, and metrics to assess and/or guarantee a certain level of privacy. They will be introduced to the properties and metrics related to anonymization (e.g., k-anonymity, l-diversity), data aggregation (e.g., randomized responses, ε-differential privacy), as well as other privacy assessment methodologies (e.g., inferential privacy). Third, the course will address usability issues and the role of individuals (i.e., users) in privacy management (i.e., usable security and privacy) and the design of privacy-enhancing technologies. In this context, we will analyze the main concepts seen during the course and discuss their advantages and disadvantages in terms of usability, as well as their implementation for mass-market and large-scale technologies. Across all three parts of the course, practical exercises, as well as recent research articles reading, and presentations will be used as a complement to support the concepts seen in class, as well as to provide concrete examples of methodologies related to the assessment of privacy in general. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | N. Gerber, A. Stöver, and K. Marky, Eds., Human Factors in Privacy Research. Cham: Springer International Publishing, 2023. doi: 10.1007/978-3-031-28643-8. T. Carvalho, N. Moniz, P. Faria, and L. Antunes, “Survey on Privacy-Preserving Techniques for Microdata Publication,” ACM Comput. Surv., vol. 55, no. 14s, pp. 1–42, Dec. 2023, doi: 10.1145/3588765. A. Y. Ding, G. L. De Jesus, and M. Janssen, “Ethical hacking for boosting IoT vulnerability management: a first look into bug bounty programs and responsible disclosure,” in Proceedings of the Eighth International Conference on Telecommunications and Remote Sensing, in ICTRS ’19. New York, NY, USA: Association for Computing Machinery, Sep. 2019, pp. 49–55. doi: 10.1145/3357767.3357774. N. Gerber, P. Gerber, and M. Volkamer, “Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior,” Computers & Security, vol. 77, pp. 226–261, Aug. 2018, doi: 10.1016/j.cose.2018.04.002. A. Moallem, Ed., HCI for Cybersecurity, Privacy and Trust: 4th International Conference, HCI-CPT 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, vol. 13333. in Lecture Notes in Computer Science, vol. 13333. Cham: Springer International Publishing, 2022. doi: 10.1007/978-3-031-05563-8. M. Weulen Kranenbarg, T. J. Holt, and J. van der Ham, “Don’t shoot the messenger! A criminological and computer science perspective on coordinated vulnerability disclosure,” Crime Science, vol. 7, no. 1, p. 16, Nov. 2018, doi: 10.1186/s40163-018-0090-8. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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