Search result: Catalogue data in Spring Semester 2021

GESS Science in Perspective Information
Only the courses listed below will be recognized as "GESS Science in Perspective" courses.

Further below you will find courses under the category "Type B courses Reflections about subject specific methods and content" as well as the language courses.

During the Bachelor’s degree Students should acquire at least 6 ECTS and during the Master’s degree 2 ECTS.

Students who already took a course within their main study program are NOT allowed to take the course again.
Type B: Reflection About Subject-Specific Methods and Contents
Subject-specific courses: Recommended for bachelor students after their first-year examination and for all master- or doctoral students.

Students who already took a course within their main study program are NOT allowed to take the same course again.

All these courses are listed under the category “Typ A”, this means, every student can enroll in these courses.
D-HEST
NumberTitleTypeECTSHoursLecturers
851-0158-13LEcology and Environmentalism Restricted registration - show details
Number of participants limited to 40

Particularly suitable for students of D-ERDW, D-HEST, D-USYS, D-BIOL
W3 credits2SN. Guettler
AbstractThe notion of „ecology“ refers to both, scientific research on environments as well as their protection. But how have academic ecology and the environmental movements intersected throughout history?
ObjectiveIn the seminar, students will read and discuss key sources as well as secondary literature on the knowledge transfers between scientific ecology and the environmental movements of the 19th and 20th century. Topics range from 19th-century homeland movement and the rise of ecological awareness in colonial settings, to the rise of an environmental awareness during the Cold War, with a special focus on „green“ politics in Europe. Apart from scientists and „counter-scientists“ the seminar focuses on concepts and ideas that circulated between academic ecology and different nature movements.
The participants learn to engage historically with original texts as well as to handle independently the extensive historical literature on the history of environmentalism. At the same time, they develop a critical understanding of different political agendas that have shaped academic and popular ecology until the present day. Students also learn to communicate their findings by writing short (and fictive) blog posts on different aspects of this history.
851-0745-00LEthics Workshop: The Impact of Digital Life on Society Restricted registration - show details
Number of participants limited to 30.

Open to all Master level / PhD students.
W2 credits2SE. Vayena, A. Blasimme, C. Brall, F. Gille, M. Schneider, J. Sleigh
AbstractThis workshop focuses on understanding and managing the ethical and social issues arising from the integration of new technologies in various aspects of daily life.
ObjectiveExplain relevant concepts in ethics.
Evaluate the ethical dimensions of new technology uses.
Identify impacted stakeholders and who is ethically responsible.
Engage constructively in the public discourse relating to new technology impacts.
Review tools and resources currently available that facilitate resolutions and ethical practice
Work in a more ethically reflective way
ContentThe workshop offers students an experience that trains their ability for critical analysis and develops awareness of responsibilities as a researcher, consumer and citizen. Learning will occur in the context of three intensive workshop days, which are highly interactive and focus on the development and application of reasoning skills.

The workshop will begin with some fundamentals: the nature of ethics, of consent and big data, of AI ethics, public trust and health ethics. Students will then be introduced to key ethical concepts such as fairness, autonomy, trust, accountability, justice, as well different ways of reasoning about the ethics of digital technologies.

A range of practical problems and issues in the domains of education, news media, society, social media, digital health and justice will be then considered. These six domains are represented respectively by unique and interesting case studies. Each case study has been selected not only for its timely and engaging nature, but also for its relevance. Through the analysis of these case studies key ethical questions (such as fairness, accountability, explain-ability, access etc.) will be highlighted and questions of responsibility and tools for ethical practice will be explored. Throughout, the emphasis will be on learning to make sound arguments about the ethical aspects of policy, practice and research.
851-0097-00LWhat Is Knowledge and Under What Conditions Are We Entitled to Claim Knowledge?W3 credits2GL. Wingert
AbstractThe seminar aims at a clarification of the concept of knowledge, as it is built in our experiential relations to the world. An analysis is needed of the difference between knowledge and belief, of the relation between objectivity and knowledge, and of the role of reasons for having knowledge. Additionally, the legitimacy of different types of knowledge claims should be evaluated.
ObjectiveOn will able to evaluate the arguments pro and con the thesis, that knowledge is justified, true belief. Furthermore, one will gain some insights in the role of reasons for knowledge and in the merits and misgivings of a naturalistic account of knowledge. Finally, one will be a bit more familiar with some theories of philosophical epistemology (e.g. empiricism, rationalism).
D-INFK
NumberTitleTypeECTSHoursLecturers
851-0585-38LData Science in Techno-Socio-Economic Systems Restricted registration - show details
Number of participants limited to 80

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
W3 credits2VD. Helbing, N. Antulov-Fantulin, V. Vasiliauskaite
AbstractThis 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.
ObjectiveThe 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.
ContentWill be provided on a separate course webpage.
Lecture notesSlides will be provided.
LiteratureGrus, Joel. "Data Science from Scratch: First Principles with Python". O'Reilly Media, 2019.
Link

"A high-bias, low-variance introduction to machine learning for physicists"
Link

Applications to Techno-Socio-Economic Systems:

"The hidden geometry of complex, network-driven contagion phenomena" (relevant for modeling pandemic spread)
Link

"A network framework of cultural history"
Link

"Science of science"
Link

"Generalized network dismantling"
Link

Further literature will be recommended in the lectures.
Prerequisites / NoticeGood programming skills and a good understanding of probability & statistics and calculus are expected.
851-0740-00LBig Data, Law, and Policy Restricted registration - show details
Number of participants limited to 35.
Students will be informed by 1.3.2021 the latest.
W3 credits2SS. Bechtold
AbstractThis 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.
ObjectiveThis 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.
851-0732-03LIntellectual Property: An Introduction Information Restricted registration - show details
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.
W2 credits2VS. Bechtold, R. Zingg
AbstractThe 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.
ObjectiveIntellectual 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.
851-0727-01LTelecommunications Law
Particularly suitable for students of D-INFK, D-ITET
W2 credits2VC. von Zedtwitz
AbstractIntroduction 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).
ObjectiveBy 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.
Content1. 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 notesThe 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.
LiteratureNo mandatory readings.
Prerequisites / NoticeShort written exam at the end of the semester (scope and materials to be defined during the course).
851-0739-01LSequencing Legal DNA: NLP for Law and Political Economy
Particularly suitable for students of D-INFK, D-ITET, D-MTEC
W3 credits2VE. Ash
AbstractThis course explores the application of natural language processing techniques to texts in law, politics, and the news media.
ObjectiveStudents 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.
ContentNLP 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 / NoticeSome programming experience in Python is required, and some experience with NLP is highly recommended.
851-0739-02LSequencing Legal DNA: NLP for Law and Political Economy (Course Project)
This is the optional course project for "Building a Robot Judge: Data Science for the Law."

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.
W2 credits2VE. Ash
AbstractThis is the companion course for extra credit for a course project, for the course "Sequencing Legal DNA: NLP for Law and Political Economy".
ObjectiveStudents 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.
851-0165-00LQuestions Concerning the Philosophy of Mathematics, Theoretical Physics and Computer Science Restricted registration - show details W3 credits2SG. Sommaruga, S. Wolf
AbstractThis seminar tackles questions of the philosophy of mathematics, of theoretical physics ad computer science which are rather non-standard such as: Are proofs really constitutive of mathematics? Why are applications of mathematics (to nature but also to mathematics itself) so fascinating and so hard to understand? etc.
ObjectiveThe objective is not so much to get acquainted with basic concepts and theories in the philosophy of mathematics, of theoretical physics and computer science, but to reflect in a methodical way about what lies at the origin of these philosophies. Students should learn to articulate questions arising during their studies and to pursue them in a more systematic way.
ContentThis seminar tackles questions of the philosophy of mathematics, of theoretical physics ad computer science which are rather non-standard such as: Are proofs really constitutive of mathematics? Why are applications of mathematics (to nature but also to mathematics itself) so fascinating and so hard to understand? Why do certain physical theories, e.g. quantum mechanics, need an "interpretation" whereas others don't? Is computer science part of discrete mathematics or a natural science? etc.
851-0173-00LHistory of Formal Logic: The Emergence of Boolean Logic Restricted registration - show details W3 credits2VJ. L. Gastaldi
AbstractThe invention of Boolean logic in the middle of the 19th century is considered a major event in the history of modern thought. However, Boole’s original system does not correspond to what we came to understand as Boolean logic.
We will study the early history of Boolean logic in relation to the mathematics of its epoch, in search of an alternative philosophy of formal knowledge for the present.
ObjectiveDuring the course, students will be able to:
-Acquire a general perspective on the history of formal logic
-Review relevant aspects of the history of modern mathematics
-Obtain philosophical and historical tools for critically assessing the status of formal sciences
-Develop a critical understanding of the notion of formal
-Discuss the methodological capabilities of historical epistemology
ContentThe invention of Boolean logic in the middle of the 19th century is considered a major event in the history of modern thought. Boolean algebras and Boolean rings lay at the basis of propositional logic and digital communication, contributing in a decisive way to the theoretical and technical conditions of our time. However, if attention is paid to Boole’s own work, it will quickly appear that his Calculus of Logic does not correspond to what we came to understand as Boolean logic. Instead of disregarding those differences as inevitable mistakes of any pioneering enterprise, waiting to be corrected by successive developments, we will try to understand them as the sign of an alternative philosophy of logic and formal knowledge, which later developments excluded and forgot, and from which recent advances in formal sciences could take advantage. Such an inquiry will give us the occasion of exploring the philosophical and scientific landscape in which formal logic emerged in the first half of the 19th century (focusing on the works of Babbage, De Morgan and Boole), and to build a critical perspective on the notion of “formal”, at the crossroad of the history and philosophy of mathematics and logic.
851-0174-00LRebooting AI: Human and Social Aspects of Artificial Intelligence Restricted registration - show details
Suitable only for MA and PhD students
W3 credits2GJ. L. Gastaldi, O. Del Fabbro, A. Nardo, D. Trninic
AbstractSeveral researchers from the humanities will propose a critical yet not partisan approach to AI, aiming at elaborating a common perspective on this phenomenon. Sessions will delve into aspects of the way in which AI challenges our understanding of the human, such as “Knowledge”, “Learning”, “Language”, “Freedom” or “Justice”.
ObjectiveDuring the course, students will be able to:
-Discuss relevant aspects of the impact of AI in human and social life
-Obtain theoretical and methodological tools for critically assessing the place of technology in society
-Develop a critical understanding of the conceptual grounds of AI
-Acquire a general perspective on the different fields and points of views in the humanities
-Engage in collaborative work with researchers in the humanities
ContentThe last decades have witnessed a remarkable development in the field of Artificial Intelligence (AI). Although mainly technical feat, such advances have decisive consequences in a wide variety of aspects of human and social life. Even more, AI is challenging in multiple ways our very understanding of what is to be a human. However, despite the significance of the transformations at stake, the perspectives of the humanities -traditionally established as a valid source of critical inquiry into human matters- are generally relegated to a secondary role in the development of AI.

In this seminar, several researchers from the humanities will propose a critical yet not partisan approach to AI, aiming at elaborating a common perspective which could be taken as a legitimate interlocutor in the debates arising around the current stakes of technology in our society. The seminar will take the form of presentations based on critical readings of chosen texts, followed by group discussions. Each session will delve into one aspect of the way in which AI challenges our understanding of the human, such as “Knowledge”, “Learning”, “Language”, “Freedom” or “Justice”, confronting how they are dealt with in state-of-the-art texts in AI and relevant works in the humanities.

We expect students from science, technology, engineering, and mathematics and other fields outside the humanities to actively contribute to a collective construction, which could lead to further collaboration within but also outside this course.

As part of the Turing Centre, this seminar intends to sow the seed of a suitable and long-term environment for the exchange of ideas between multiple fields in the natural sciences and the humanities.

The seminar will be conducted by Olivier Del Frabbro, Juan Luis Gastaldi, Aline Nardo, Vanessa Rampton and Dragan Trninic.
Prerequisites / NoticeSuitable only for MA and PhD students
D-ITET
NumberTitleTypeECTSHoursLecturers
851-0585-38LData Science in Techno-Socio-Economic Systems Restricted registration - show details
Number of participants limited to 80

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
W3 credits2VD. Helbing, N. Antulov-Fantulin, V. Vasiliauskaite
AbstractThis 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.
ObjectiveThe 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.
ContentWill be provided on a separate course webpage.
Lecture notesSlides will be provided.
LiteratureGrus, Joel. "Data Science from Scratch: First Principles with Python". O'Reilly Media, 2019.
Link

"A high-bias, low-variance introduction to machine learning for physicists"
Link

Applications to Techno-Socio-Economic Systems:

"The hidden geometry of complex, network-driven contagion phenomena" (relevant for modeling pandemic spread)
Link

"A network framework of cultural history"
Link

"Science of science"
Link

"Generalized network dismantling"
Link

Further literature will be recommended in the lectures.
Prerequisites / NoticeGood programming skills and a good understanding of probability & statistics and calculus are expected.
227-0664-00LTechnology and Policy of Electrical Energy StorageW3 credits2GV. Wood, T. Schmidt
AbstractWith the global emphasis on decreasing CO2 emissions, achieving fossil fuel independence and growing the use of renewables, developing & implementing energy storage solutions for electric mobility & grid stabilization represent a key technology & policy challenge. This course uses lithium ion batteries as a case study to understand the interplay between technology, economics, and policy.
ObjectiveThe students will learn of the complexity involved in battery research, design, production, as well as in investment, economics and policy making around batteries. Students from technical disciplines will gain insights into policy, while students from social science backgrounds will gain insights into technology.
ContentWith the global emphasis on decreasing CO2 emissions, achieving fossil fuel independence, and integrating renewables on the electric grid, developing and implementing energy storage solutions for electric mobility and grid stabilization represent a key technology and policy challenge. The class will focus on lithium ion batteries since they are poised to enter a variety of markets where policy decisions will affect their production, adoption, and usage scenarios. The course considers the interplay between technology, economics, and policy.

* intro to energy storage for electric mobility and grid-stabilization
* basics of battery operation, manufacturing, and integration
* intro to the role of policy for energy storage innovation & diffusion
* discussion of complexities involved in policy and politics of energy storage
Lecture notesMaterials will be made available on the website.
LiteratureMaterials will be made available on the website.
Prerequisites / NoticeStrong interest in energy and technology policy.
851-0740-00LBig Data, Law, and Policy Restricted registration - show details
Number of participants limited to 35.
Students will be informed by 1.3.2021 the latest.
W3 credits2SS. Bechtold
AbstractThis 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.
ObjectiveThis 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.
851-0252-01LHuman-Computer Interaction: Cognition and Usability Restricted registration - show details
Number of participants limited to 40.

Particularly suitable for students of D-ITET
W3 credits2SC. Hölscher, S. Credé, H. Zhao
AbstractThis seminar introduces theory and methods in human-computer interaction and usability. Cognitive Science provides a theoretical framework for designing user interfaces as well as a range of methods for assessing usability (user testing, cognitive walkthrough, GOMS). The seminar will provide an opportunity to experience some of the methods in applied group projects.
ObjectiveThis seminar will introduce key topics, theories and methodology in human-computer interaction (HCI) and usability. Presentations will cover the basics of human-computer interaction and selected topics like mobile interaction, adaptive systems, human error and attention. A focus of the seminar will be on getting to know evaluation techniques in HCI. Students will work in groups and will first familiarize themselves with a select usability evaluation method (e.g. user testing, GOMS, task analysis, heuristic evaluation, questionnaires or Cognitive Walkthrough). They will then apply the methods to a human-computer interaction setting (e.g. an existing software or hardware interface) and present the method as well as their procedure and results to the plenary. Active participation is vital for the success of the seminar, and students are expected to contribute to presentations of foundational themes, methods and results of their chosen group project. In order to obtain course credit a written essay / report will be required (details to be specified in the introductory session of the course).
851-0732-03LIntellectual Property: An Introduction Information Restricted registration - show details
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.
W2 credits2VS. Bechtold, R. Zingg
AbstractThe 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.
ObjectiveIntellectual 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.
851-0727-01LTelecommunications Law
Particularly suitable for students of D-INFK, D-ITET
W2 credits2VC. von Zedtwitz
AbstractIntroduction 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).
ObjectiveBy 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.
Content1. 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 notesThe 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.
LiteratureNo mandatory readings.
Prerequisites / NoticeShort written exam at the end of the semester (scope and materials to be defined during the course).
860-0022-00LComplexity and Global Systems Science Restricted registration - show details
Number of participants limited to 50.

Prerequisites: solid mathematical skills.

Particularly suitable for students of D-ITET, D-MAVT and ISTP
W3 credits2SD. Helbing, S. Mahajan
AbstractThis 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.
ObjectiveParticipants 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.
ContentThis 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
LiteraturePhilip Ball
Why Society Is A Complex Matter
Link

Globally networked risks and how to respond
Nature: Link

Global Systems Science and Policy
Link

Managing Complexity: Insights, Concepts, Applications
Link

Further links:

Link

Link

Link

Link

Further literature will be recommended in the lectures.
Prerequisites / NoticeMathematical skills can be helpful
851-0739-01LSequencing Legal DNA: NLP for Law and Political Economy
Particularly suitable for students of D-INFK, D-ITET, D-MTEC
W3 credits2VE. Ash
AbstractThis course explores the application of natural language processing techniques to texts in law, politics, and the news media.
ObjectiveStudents 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.
ContentNLP 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 / NoticeSome programming experience in Python is required, and some experience with NLP is highly recommended.
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