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The Opportunities, Limitations, and Challenges in Using Machine Learning Technologies for Humanitarian Work and Development
Title / Series / Name
Publication Volume
Publication Issue
Pages
Editors
Keywords
Humanitarian work
artificial intelligence
complex systems
development
machine learning
Control and Systems Engineering
artificial intelligence
complex systems
development
machine learning
Control and Systems Engineering
URI
https://hdl.handle.net/20.500.14018/26512
Abstract
Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity's most pressing issues has garnered interest outside the traditional disciplines studying and working on international development. Today, scientific communities in fields like Computational Social Science, Network Science, Complex Systems, Human Computer Interaction, Machine Learning, and the broader AI field are increasingly starting to pay attention to these pressing issues. However, are sophisticated data driven tools ready to be used for solving real-world problems with imperfect data and of staggering complexity? We outline the current state-of-the-art and identify barriers, which need to be surmounted in order for data-driven technologies to become useful in humanitarian and development contexts. We argue that, without organized and purposeful efforts, these new technologies risk at best falling short of promised goals, at worst they can increase inequality, amplify discrimination, and infringe upon human rights.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2024-05-03
Language
ISBN
Identifiers
10.1142/s0219525924400022