Dirk Helbing: Katalogdaten im Frühjahrssemester 2023

NameHerr Prof. Dr. Dirk Helbing
LehrgebietComputational Social Science
Adresse
Computational Social Science
ETH Zürich, STD F 3
Stampfenbachstrasse 48
8092 Zürich
SWITZERLAND
Telefon+41 44 632 88 80
Fax+41 44 632 17 67
E-Maildirk.helbing@gess.ethz.ch
DepartementGeistes-, Sozial- und Staatswissenschaften
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
851-0252-04LBehavioral Studies Colloquium Information 0 KP2KC. Hölscher, U. Brandes, D. Helbing, M. Kapur, C. Stadtfeld, E. Stern, V. Zimmermann
KurzbeschreibungThis 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.
LernzielParticipants are informed about recent and ongoing research in different branches of the behavioral sciences. Presenting doctoral students obtain feedback on their dissertation research plan.
InhaltThis 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.
Voraussetzungen / BesonderesDoctoral students in D-GESS can obtain 1 credit point for presenting their research in the colloquium.
851-0585-38LData Science in Techno-Socio-Economic Systems Belegung eingeschränkt - Details anzeigen
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 KP2VD. Helbing, N. Antulov-Fantulin, V. Vasiliauskaite
KurzbeschreibungThis 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.
LernzielThe 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.
InhaltWill be provided on a separate course webpage.
SkriptSlides will be provided.
LiteraturGrus, 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.
Voraussetzungen / BesonderesSubstantial programming skills and knowledge of statistical methods are expected.

We recommend this course for students in the 4th semester or above.

Students need to present a new subject, for which they have not earned any credit points before.

Good scientific practices, in particular citation and quotation rules, must be properly complied with.

Chatham House rules apply to this course. Materials may not be shared without previous written permission.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengeprüft
Problemlösunggeprüft
Projektmanagementgeprüft
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgeprüft
Kundenorientierunggefördert
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt geprüft
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft
851-0585-48LControversies in Game Theory Belegung eingeschränkt - Details anzeigen 3 KP2VD. Helbing, H. Nax, H. Rauhut
KurzbeschreibungThe mini-course 'Controversies in Game Theory' consists of four 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.
LernzielStudents 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.
InhaltThe 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.
SkriptSlides will be provided.
LiteraturJohn 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.
Voraussetzungen / BesonderesThis course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulation.

Good scientific practices, in particular citation and quotation rules, must be properly complied with.

Chatham House rules apply to this course. Materials may not be shared without previous written permission.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengeprüft
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggefördert
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt geprüft
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft
860-0022-00LComplexity and Global Systems Science Belegung eingeschränkt - Details anzeigen
Prerequisites: solid mathematical skills.

Particularly suitable for students of D-ITET, D-MAVT and ISTP
3 KP2SD. Helbing, C. Carissimo, A. Musso
KurzbeschreibungThis 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.
LernzielParticipants 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.
InhaltThis 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.
Skript"Social Self-Organization
Agent-Based Simulations and Experiments to Study Emergent Social Behavior"
Helbing, Dirk
ISBN 978-3-642-24004-1
LiteraturPhilip 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.
Voraussetzungen / BesonderesMathematical skills can be helpful.

Students need to present a new subject, for which they have not earned any credit points before.

Good scientific practices, in particular citation and quotation rules, must be properly complied with.

Chatham House rules apply to this course. Materials may not be shared without previous written permission.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengeprüft
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt geprüft
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft
860-0024-00LDigital Society: Ethical, Societal and Economic Challenges Belegung eingeschränkt - Details anzeigen 3 KP2VD. Helbing, S. Mahajan
KurzbeschreibungThis 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.
LernzielParticipants 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.
InhaltWill be provided on Moodle.
SkriptWill be provided on Moodle.
LiteraturEthically 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/

Ethics of smart cities
https://www.mdpi.com/2071-1050/13/20/11162

The ethics of AI in health care: a mapping review
https://www.sciencedirect.com/science/article/pii/S0277953620303919

Soft Ethics and the Governance of the Digital
https://link.springer.com/article/10.1007/s13347-018-0303-9

The Ethics of AI Ethics: An Evaluation of Guidelines
https://link.springer.com/article/10.1007/s11023-020-09517-8

Principles of robotics: regulating robots in the real world
https://www.tandfonline.com/doi/full/10.1080/09540091.2016.1271400

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation
https://arxiv.org/abs/1802.07228

Will Democracy Survive Big Data and Artificial Intelligence?
https://link.springer.com/chapter/10.1007/978-3-319-90869-4_7

Further literature will be recommended in the lectures.
Voraussetzungen / BesonderesTo 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.
Students need to present a new subject, for which they have not earned any credit points before.

Good scientific practices, in particular citation and quotation rules, must be properly complied with.

Chatham House rules apply to this course. Materials may not be shared without previous written permission.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengeprüft
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgefördert
Kundenorientierunggefördert
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt geprüft
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft