Our courses on AI ethics, policy, and governance

This workshop focuses on understanding and managing the ethical and social issues arising from the integration of new technologies in various aspects of daily life.

This course provides students doing their own research on topics in science, technology and society with focused peer-feedback and tailored theoretical and methodological discussions to support the development of their projects.

This course integrates computer science with peace and security, global health, and climate science. Students will apply their skills to real-world data projects addressing global challenges, while critically examining the ethical and societal impact of AI in these domains.

This course explores the application of natural language processing techniques to texts in law, politics, and the news media. Students will put these tools to work in a course project.

Visual analytics​​ supports the design of human-in-the-loop interfaces that enable human-machine collaboration. In this course, will go through the fundamentals of designing interactive visualizations, later applying them to explain and interact with machine learning models.

This course introduces students to societal perspectives on the artificial intelligence 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.

The course provides an introduction into the concepts and tools of ethics with a special emphasis on ethical dilemmas in biomedicine and drug development.

Technological change, i.e. the innovation and diffusion of new technologies, is a fundamental driver of economic growth but can also have detrimental side effects. This module introduces methods to assess technology-related policy alternatives and to analyse how policies affect technological changes and society.

Module in the CAS in Machine Learning in Finance and Insurance

Understand the philosophical underpinnings of natural language processing (NLP), most of which centered around statistical machine learning applied to natural language data.

Generative AI is transforming education. Discover how to harness its power to create engaging,

This workshop focuses on helping you find the right tools for your scientific writing project. We will discuss the key differences of the main currently available large language models so that you can select the most suitable one. We will outline what tasks are the most suited for AI assistance and how effective prompting techniques can help. Further topics are image generation and literature review tools. During the course, you will have the opportunity to collect hands-on experiences.

This introductory two-day course explores the potential and challenges of AI in contributing to sustainable and equitable development. Participants will learn about AI's applications in various fields, including healthcare, agriculture, and education, while addressing ethical concerns such as data privacy and algorithmic bias.

A comprehensive programme to gain insight into the world of generative artificial intelligence. It promotes competent handling of it and highlights various aspects in lunchtime events and a comprehensive self-study programme.

This short course offers a critical overview and understanding of the ethical and regulatory challenges triggered by the use of big data and artificial intelligence (AI) in the health sector.

This course focuses on achieving impact and innovation with data science. It features theoretical lectures on selected applications of data science, practical lectures on leveraging data science within a business context, and a selection of exemplary use cases from the private and public sector.

This course introduces students to the ethical, political and legal debates and transformations in relation to Artificial Intelligence and provides students with concepts and methods from the constructivist and interpretive social sciences to work towards responsible and democratic human-technology futures.

This course explores how generative AI intersects with and challenges copyright, contract, privacy, and competition law. Focusing on Swiss, EU, and US frameworks, students will learn to navigate the legal and ethical issues surrounding both the training data and the output of AI systems.

This course introduces core modeling techniques and algorithms from machine learning, optimization and control for reasoning and decision making under uncertainty, and study applications in areas such as robotics.

This course examines ethical problems posed by digital technologies, including cyber, information, robotics, and AI. Using concrete examples like algorithmic bias and autonomous weapons, students will learn to apply classical ethical theories to analyze and discuss these issues.

This course teaches students to apply data science, AI, and remote sensing to human rights research. It focuses on developing responsible and critical skills for using these technologies in sensitive environments, emphasizing ethics, data protection, and bias in humanitarian contexts.

Should we use this technology or not? What are the ethical opportunities and risks of this technological application? Should we always pursue all that is technically possible? What is ethics? How do ethics and technologies relate to each other? Does ethics hinder technological progress? How can ethics foster innovation? Which ethical theory should we apply in a global research-context? 

This semester course enables students to recognize, anticipate and address ethical issues in the domain of health sciences and their technological application. The students will acquire the necessary theoretical and analytic resources to develop critical thinking skills in the field of applied ethics and will practice how to use such resources to address concrete ethical issues in health sciences

Creating reliable, secure, robust, and fair machine learning models is a core challenge in artificial intelligence and one of fundamental importance. The goal of the course is to teach both the mathematical foundations of this new and emerging area as well as to introduce students to the latest and most exciting research in the space. 

This course presents current trends, analysing the risks involved in the digitisation of conflicts, both for civilians (as means and victims) and for private technology companies as the main actors of this transformation.

This interdisciplinary module, co-taught by ZHdK and ETH, explores AI as a historical-material practice.

The course fosters critical, culturally conscious reflection on AI regulation by exploring cross-cultural assessment of the concept of personhood & responsibility in digital society.

The course provides an overview of the scientific, religious, technical and philosophical debates on the human quest for the creation of artificial life and artificial intelligence. In exemplary readings with subsequent discussion, the course explores the question of which aspects of the topic literary texts since antiquity, visual art and film negotiate.

This course brings together advanced students in science, technology, and society to develop their research projects. Through peer feedback, discussions with faculty, and tailored methodological sessions, you'll gain support for your work and deepen your knowledge of core STS and moral and political theories.

This course provides an introduction to big data methods for public policy analysis. Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.

In this seminar on "Critical Thinking", students are equipped with the essential skills needed to thrive in a dynamic, confusing and ever-changing field. It explores the fundamental principles of critical thinking and its application within the realm of research and technology.

Interested in using Generative AI in your scientific work processes but in responsible and ethical responsive way? This block course for PhD students allows experimenting with generative AI to generate texts, images and audio that can be used in science from scientific presentations to publications.

In this collaborative seminar for ZHdK and ETH Students, the aim is to bring together the creative vision and the technical expertise of both of Film and Information Technology and Electrical Engineering students to collaboratively craft a plot for a short film that explores the intricate ethical questions posed by the use of AI technologies.

This course introduces students to the ethical, cultural, and political contexts and consequences of digital technologies (big data, computing, Artificial Intelligence) and equips them with an interpretive social science toolkit for critical thinking and responsible action in a digital world.