Dirk Helbing: Catalogue data in Spring Semester 2022 |
| Name | Prof. Dr. Dirk Helbing |
| Field | Computational Social Science |
| Address | Computational Social Science ETH Zürich, STD F 3 Stampfenbachstrasse 48 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 88 80 |
| Fax | +41 44 632 17 67 |
| dirk.helbing@gess.ethz.ch | |
| Department | Humanities, Social and Political Sciences |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 851-0252-04L | Behavioral Studies Colloquium  | 0 credits | 2K | E. Stern, U. Brandes, D. Helbing, C. Hölscher, M. Kapur, C. Stadtfeld | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This colloquium offers an opportunity to discuss recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. The colloquium features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Participants are informed about recent and ongoing research in different branches of the behavioral sciences. Presenting doctoral students obtain feedback on their dissertation research plan. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This colloquium offers an opportunity to discuss recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It covers a broad range of areas, including theoretical as well as empirical research in social psychology, research on higher education, sociology, modeling and simulation in sociology, decision theory and behavioral game theory, economics, research on learning and instruction, cognitive psychology and cognitive science. The colloquium features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Doctoral students in D-GESS can obtain 1 credit point for presenting their research in the colloquium. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | 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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| 851-0585-48L | Controversies in Game Theory Number of participants limited to 100. | 3 credits | 2V | D. Helbing, H. Nax, H. Rauhut | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The mini-course 'Controversies in Game Theory' consists of 5 course units that provide an in-depth introduction to issues in game theory motivated by real-world issues related to the tensions that may result from interactions in groups, where individual and collective interests may conflict. The course integrates theory from various disciplines. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students are encouraged to think about human interactions, and in particular in the context of game theory, in a way that is traditionally not covered in introductory game theory courses. The aim of the course is to teach students the complex conditional interdependencies in group interactions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course will pay special attention to the dichotomy of cooperative vs non-cooperative game theory through the lense of the pioneering work by John von Neumann (who—which is not very well known--was an undergraduate student at ETH Zurich). We will review the main solution concepts from both fields, work with applications relying on those, and look at the “Nash program” which is a famous attempt to bridge the two. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Slides will be provided. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | John v Neumann and Oskar Morgenstern. 1944. Theory of Games and Economic Behavior. (https://en.wikipedia.org/wiki/Theory_of_Games_and_Economic_Behavior) Diekmann, Andreas: Spieltheorie. Rowohlt 2009. Dixit, Avinash K., and Susan Skeath. Games of Strategy. WW Norton & Company, 2015. Ken Binmore (1992): Fun and Games. Lexington: Heath. Camerer, Colin (2003): Behavioral Game Theory. Experiments in Strategic Interaction. Princeton: Princeton University Press. Game Theory Evolving https://www.amazon.com/Game-Theory-Evolving-Problem-Centered-Introduction/dp/0691140510/ Evolutionary Game Theory https://www.amazon.com/Evolutionary-Game-Theory-MIT-Press/dp/0262731215/ Evolutionary Game Theory in Natural, Social and Virtual Worlds https://www.amazon.com/Evolutionary-Natural-Social-Virtual-Worlds/dp/0199981159/ Evolutionary Dynamics and Extensive Form Games https://www.amazon.com/Evolutionary-Dynamics-Extensive-Economic-Evolution/dp/0262033054/ Evolutionary Games and Population Dynamics https://www.amazon.com/Evolutionary-Games-Population-Dynamics-Hofbauer-dp-0521623650/ Quantitative Sociodynamics https://www.springer.com/gp/book/9783642115455 Synergistic Selection: How Cooperation Has Shaped Evolution and the Rise of Humankind https://www.amazon.com/Synergistic-Selection-Cooperation-Evolution-Humankind-ebook/dp/B07BHL7P43/ Survival of the Nicest https://www.amazon.com/Survival-Nicest-Altruism-Human-Along/dp/1615190902/ Evolutionary Games with Sociophysics https://www.amazon.com/Evolutionary-Games-Sociophysics-Epidemics-Complexity-dp-9811327688/dp/9811327688/ Statistical Physics and Computational Methods for Computational Game Theory https://www.amazon.com/Statistical-Computational-Evolutionary-SpringerBriefs-Complexity/dp/3319702041/ Games of life https://www.amazon.com/Games-Life-Explorations-Evolution-Behaviour/dp/0198547838 Further literature will be recommended in the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 860-0022-00L | Complexity and Global Systems Science Number of participants limited to 50. Prerequisites: solid mathematical skills. Particularly suitable for students of D-ITET, D-MAVT and ISTP | 3 credits | 2S | D. Helbing, S. Mahajan | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course discusses complex techno-socio-economic systems, their counter-intuitive behaviors, and how their theoretical understanding empowers us to solve some long-standing problems that are currently bothering the world. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Participants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop models for open problems, to analyze them, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to think scientifically about complex dynamical systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | This course starts with a discussion of the typical and often counter-intuitive features of complex dynamical systems such as self-organization, emergence, (sudden) phase transitions at "tipping points", multi-stability, systemic instability, deterministic chaos, and turbulence. It then discusses phenomena in networked systems such as feedback, side and cascading effects, and the problem of radical uncertainty. The course progresses by demonstrating the relevance of these properties for understanding societal and, at times, global-scale problems such as traffic jams, crowd disasters, breakdowns of cooperation, crime, conflict, social unrests, political revolutions, bubbles and crashes in financial markets, epidemic spreading, and/or "tragedies of the commons" such as environmental exploitation, overfishing, or climate change. Based on this understanding, the course points to possible ways of mitigating techno-socio-economic-environmental problems, and what data science may contribute to their solution. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | "Social Self-Organization Agent-Based Simulations and Experiments to Study Emergent Social Behavior" Helbing, Dirk ISBN 978-3-642-24004-1 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Philip Ball Why Society Is A Complex Matter https://www.springer.com/gp/book/9783642289996 Globally networked risks and how to respond Nature: https://www.nature.com/articles/nature12047 Global Systems Science and Policy https://library.oapen.org/bitstream/handle/20.500.12657/28004/1001993.pdf?sequence=1#page=214 Managing Complexity: Insights, Concepts, Applications https://www.springer.com/gp/book/9783540752608 Further links: http://global-systems-science.org http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS-06-06-2013-F1.pdf http://www.global-systems-science.org/wp-content/uploads/2013/06/GSS_SynthesisPaper_070613_final.pdf https://ec.europa.eu/digital-single-market/en/global-systems-science Further literature will be recommended in the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Mathematical skills can be helpful | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 860-0024-00L | Digital Society: Ethical, Societal and Economic Challenges Number of participants is limited to 30. | 3 credits | 2V | D. Helbing, C. I. Hausladen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This seminar will address ethical challenges coming along with new digital technologies such as cloud computing, Big Data, artificial intelligence, cognitive computing, quantum computing, robots, drones, Internet of Things, virtual reality, blockchain technology, and more... | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Participants shall learn to understand that any technology implies not only opportunities, but also risks. It is important to understand these well in order to minimize the risks and maximize the benefits. In some cases, it is highly non-trivial to identify and avoid undesired side effects of technologies. The seminar will sharpen the attention how to design technologies for values, also called value-sensitive design or ethically aligned design. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Will be provided on a complementary website of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Will be provided on a complementary website of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Ethically Aligned Design Version 1: https://standards.ieee.org/content/dam/ieee-standards/standards/web/documents/other/ead_v1.pdf Version 2: https://standards.ieee.org/content/dam/ieee-standards/standards/web/documents/other/ead_v2.pdf Value-Sensitive Design https://www.amazon.com/Value-Sensitive-Design-Technology-Imagination-ebook/dp/B08BT4F6L2/ Handbook of Ethics, Values and Technological Design https://www.amazon.com/Handbook-Ethics-Values-Technological-Design/dp/9400769695/ Thinking Ahead https://www.springer.com/gp/book/9783319150772 Towards Digital Enlightenment https://link.springer.com/book/10.1007/978-3-319-90869-4 Künstliche Intelligenz und Maschinisierung des Menschen https://www.amazon.com/Künstliche-Intelligenz-Maschinisierung-Menschen/dp/3869625120 Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy (J Taplin) https://bookshop.org/books/move-fast-and-break-things-how-facebook-google-and-amazon-cornered-culture-and-undermined-democracy How Humans Judge Machines https://www.amazon.co.uk/Humans-Judge-Machines-Cesar-Hidalgo/dp/0262045524/ Further literature will be recommended in the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | To earn credit points, students will have to read the relevant literature on one of the above technologies and give a presentation about the ethical implications. Both, potential problems and possible solutions shall be carefully discussed. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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