THE OPPORTUNITIES, LIMITATIONS, AND CHALLENGES IN USING MACHINE LEARNING TECHNOLOGIES FOR HUMANITARIAN WORK AND DEVELOPMENT

Vedran Sekara, Mã Rton Karsai, Esteban Moro, Dohyung Kim, Enrique Delamonica, Manuel Cebrian, Miguel Luengo-Oroz, Rebeca Moreno Jimã‰nez and Manuel Garcia-Herranz ()
Additional contact information
Vedran Sekara: IT University of Copenhagen, Copenhagen, Denmark†UNICEF, New York, NY, USA
Mã Rton Karsai: ��Central European University, Vienna, Austria§National Laboratory of Health Security, HUN-REN Rényi Institute of Mathematics, Budapest, Hungary
Esteban Moro: �Network Science Institute, Northeastern University, Boston, MA, USA
Dohyung Kim: ��UNICEF, New York, NY, USA
Enrique Delamonica: ��UNICEF, New York, NY, USA
Manuel Cebrian: ��Department of Statistics, Universidad Carlos III de Madrid, Madrid, Spain**Center for Automation and Robotics, Spanish National Research Council, Madrid, Spain
Miguel Luengo-Oroz: ��†United Nations Global Pulse, New York, USA
Rebeca Moreno Jimã‰nez: ��‡UNHCR, Geneva, Switzerland
Manuel Garcia-Herranz: ��UNICEF, New York, NY, USA

Advances in Complex Systems (ACS), 2024, vol. 27, issue 03, 1-16

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.

Keywords: Humanitarian work; development; artificial intelligence; machine learning; complex systems (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219525924400022

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