Developing AI predictive migration tools to enhance humanitarian support
The EUMigraTool (EMT) provides short-term and mid-term predictions of asylum seekers arriving in the European Union, drawing on multiple sources of public information and with a focus on human rights. After 3 years of development, it has been tested in real environments by 17 NGOs working with migra...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:304361 |
| Acceso en línea: | https://ddd.uab.cat/record/304361 https://dx.doi.org/urn:doi:10.1017/dap.2024.76 |
| Access Level: | acceso abierto |
| Palabra clave: | Predictive tools Migration Humanitarian tools EUMigraTool Artificial intelligence |
| Sumario: | The EUMigraTool (EMT) provides short-term and mid-term predictions of asylum seekers arriving in the European Union, drawing on multiple sources of public information and with a focus on human rights. After 3 years of development, it has been tested in real environments by 17 NGOs working with migrants in Spain, Italy, and Greece. This paper will first describe the functionalities, models, and features of the EMT. It will then analyze the main challenges and limitations of developing a tool for non-profit organizations, focusing on issues such as (1) the validation process and accuracy, and (2) the main ethical concerns, including the challenging exploitation plan when the main target group are NGOs. The overall purpose of this paper is to share the results and lessons learned from the creation of the EMT, and to reflect on the main elements that need to be considered when developing a predictive tool for assisting NGOs in the field of migration. |
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