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851-0691-00L 3 Credits DS D-GESS
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Human-Centered AI for Social Good: Peace, Health, Climate

Lecturers & Examiners: Prof. Dr. Andreas Wenger, Prof. Dr. Effy Vayena, Dr. Lukas Gudmundsson, Prof. Dr. Allard Duursma, Prof. Dr. Menna El-Assady, Prof. Dr. Livia Schubiger, Dr. Sara Kijewski
VVZ CR n/a

Last Updated: 2026-06-01 11:34:02

Abstract

This is an interdisciplinary course at the intersection of computer science, peace and security, global health, and climate science. Students will implement practical projects that involve the application of their skills on public data to address global challenges. In addition, students will critically engage with the ethical, social, and political implications of using AI for global challenges.

Objective

At the end of this course, students will be able to: -Apply machine learning methods of human-centered AI to global challenges. -Critically analyze the ethical implications of AI applications. -Collaborate effectively in interdisciplinary teams to develop innovative solutions. -Design, develop, and present prototypes that demonstrate the application of AI to real-world problems.

Content

This is an interdisciplinary course at the intersection of computer science, peace and security, global health, and climate science. The course is taught in the context of the memorandum of understanding between ETH Zurich and the United Nations. Students will implement practical projects that involve the application of their skills on public data to address global challenges. In addition, students will critically engage with the ethical, social, and political implications of using AI for global challenges, including issues of fairness, accountability, transparency, and potential biases inherent in AI models. They will examine both the potential and limitations of AI-driven solutions, particularly in complex, real-world contexts where technological interventions may have unintended societal consequences. This is a block course that is organized in two stages. The first stage provides the students with a theoretical and practical background needed to successfully complete the course. This stage consists of a series of seminars on topics related to the three tracks (peace, health, and climate) and computer science during the week before the spring semester starts. These seminars can be classified in three areas: (1) introductions on the field of each of the three tracks and computer science that sketch possible research directions; (2) an overview of past practical projects that showcase the practical skills required to implement interdisciplinary research projects; (3) a series of meetings with experts to discuss possible ideas for the practical research projects, integrating critical perspectives on AI ethics and societal impacts. After the first week of seminars, the course will shift the focus to designing and implementing practical projects where students can apply their skills on public data problems. These practical projects are aimed at delivering prototypes that can showcase the use of human-centered AI for global challenges related to peace, climate, and health. These practical projects are aimed at delivering prototypes that not only demonstrate the use of human-centered AI for global challenges related to peace, climate, and health, but also reflect on the ethical and social complexities involved in deploying AI-based solutions across diverse global contexts.

Resources

Learning Materials (Links)

General Information

Language
English
Levels
DS
Frequency
Yearly recurring

Examination

Type
graded semester performance

Registration & Places

Max Places
80

Course Components

Type Title Time & Place Hours
exercise Human-Centered AI for Social Good: Peace, Health, Climate
  • 24.02 Date 09:15-12:00 (HG E 7)
  • 03.03 Date 10:15-16:00 (ML H 37.1)
  • 04.03 Date 13:15-17:00 (CHN F 42)
24 h semesterly

Offered In

  • Wissenschaft im Kontext (Science in Perspective) (In Kursen aus dem Programm “Wissenschaft im Kontext” lernen Studierende, die MINT Fächer der ETH aus der Perspektive der Geistes-, Sozial- und Staatswissenschaften zu reflektieren. Nur die in diesem Abschnitt aufgelisteten Fächer können als "Wissenschaft im Kontext" angerechnet werden.)