Dagstuhl-Seminar 24082
AI for Social Good
( 18. Feb – 23. Feb, 2024 )
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https://www.dagstuhl.de/24082
Organisatoren
- Claudia Clopath (Imperial College London, GB)
- Ruben De Winne (Oxfam Novib - The Hague, NL)
- Mohammad Emtiyaz Khan (RIKEN - Tokyo, JP)
- Jacopo Margutti (510 / Netherlands Red Cross - The Hague, NL)
Kontakt
- Michael Gerke (für wissenschaftliche Fragen)
- Simone Schilke (für administrative Fragen)
Dagstuhl Reports
As part of the mandatory documentation, participants are asked to submit their talk abstracts, working group results, etc. for publication in our series Dagstuhl Reports via the Dagstuhl Reports Submission System.
- Upload (Use personal credentials as created in DOOR to log in)
Gemeinsame Dokumente
- Dagstuhl Materials Page (Use personal credentials as created in DOOR to log in)
Artificial intelligence and machine learning have made impressive strides in the last decade and – especially in the eyes of the general public – even in the last months, with innovations that have entered the daily life of billions of people. Given the magnitude of the impact of AI, the social good should not be an afterthought: market forces alone may not guarantee that these technologies benefit everyone. Instead, we believe that AI should empower those already championing humanitarian and development causes. In order to accelerate adoption of AI methods where their impact on the social good is largest, we propose to bring together non-governmental organizations working in international development and on humanitarian issues, with AI technical experts (academics, researchers, data scientists, engineers).
Primary objectives of this Dagstuhl Seminar are to establish partnerships and build trust, to iterate on concrete problems in a hands-on hackathon, and to demonstrate what is feasible today via case studies. Secondary objectives include scoping out new research challenges for the AI community to bite their teeth into, sharing methodological insights and publicizing efforts in the AI for Social Good space more generally. And of course, publication impact is substantially enhanced when a method has real-world impact. We believe that the intimacy of the Dagstuhl venue is perfect for constructive communication and exchange. We aim for the following possible outcomes:
- Direct impact NGOs by bringing state-of-the-art AI techniques to bear on their challenges, including concrete pilot showcase(s) developed in the hackathon part of the seminar.
- New research directions in machine learning that are grounded in today’s and tomorrow’s needs of NGOs (e.g., missing data, side-effects, sparse feedback, multiple competing objectives)
- New collaborations between NGOs and academics (possibly via their students) to create opportunities for long-term research that don’t end with the seminar.
- Visibility and acceptance of these ideas within the NGO sector and the AI community at large.
- Facilitation of future meetings by reflecting on the interdisciplinary process, extracting guidelines, identifying common challenges and disseminating them, e.g., in the form of a handbook.
Creative Commons BY 4.0
Claudia Clopath, Ruben De Winne, Mohammad Emtiyaz Khan, and Jacopo Margutti
- Asma Atamna (Ruhr-Universität Bochum, DE)
- Annabelle Behnke (Deutsches Rotes Kreuz e.V. - Berlin, DE)
- Siu Lun Chau (CISPA - Saarbrücken, DE)
- Claudia Clopath (Imperial College London, GB) [dblp]
- Jorn Dallinga (WWF - Zeist, NL)
- Ruben De Winne (Oxfam Novib - The Hague, NL) [dblp]
- Michael Dhatemwa (Oxfam Novib - The Hague, NL)
- Daphne Ezer (University of York, GB) [dblp]
- Elshad Gojayev (Internews - Washington, US)
- Frank Hutter (Universität Freiburg, DE) [dblp]
- Roberto Interdonato (CIRAD - Montpellier, FR)
- Mohammad Emtiyaz Khan (RIKEN - Tokyo, JP) [dblp]
- Isabell Klipper (Deutsches Rotes Kreuz e.V. - Berlin, DE)
- Parvathy Krishnan (Analytics for a Better World - Amsterdam, NL)
- Derek Loots (Médecins Sans Frontières - Amsterdam, NL)
- Subhransu Maji (University of Massachusetts - Amherst, US)
- Jacopo Margutti (510 / Netherlands Red Cross - The Hague, NL)
- Marieke Meeske (Tilburg University, NL & Oxfam Novib - Den Haag, NL)
- Krikamol Muandet (CISPA - Saarbrücken, DE) [dblp]
- Virginia Patridge (University of Massachusetts - Amherst, US)
- Julia Proskurnia (Google - Zürich, CH) [dblp]
- Lennart Purucker (Universität Freiburg, DE)
- Jake Robertson (Universität Freiburg, DE)
- Andrés Roure Cuzzoni (Propel - Den Haag, NL)
- Tom Schaul (Google DeepMind - London, GB) [dblp]
- Jeremy Springman (University of Pennsylvania - Philadelphia, US)
- Maïna Vergonjanne (Droits Quotidiens Legal Tech - Montpellier, FR)
Verwandte Seminare
Klassifikation
- Artificial Intelligence
- Computers and Society
- Machine Learning
Schlagworte
- artificial intelligence
- machine learning
- social good
- non-governmental organizations
- interdisciplinary
