A Mixed Blessing: Big Data and AI for Migration
How can migration be studied with big data and AI? What methodologies have been applied so far and what are the challenges?
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Migration research covers a wide range of disciplines and is typically conducted using different types of data, such as census data, registers and surveys, collected by government agencies and national statistical offices. These data suffer from a series of limitations regarding resolution in time and space, making the analysis of a cross-border phenomenon like migration far from straightforward.
Some promising contributions of the use of big data in migration research could include:
- studying patterns of temporary or circular migration
- timely monitoring of public opinion or media discourse on migration
- improving opinion polls
- providing evidence on aspects of migration of which we currently have limited knowledge, such as
- the integration prospects of recently arrived migrants in a country or
- future migration movements related to political or environmental conflicts.
New attempts to use big data analysis to understand human mobility and migration are promising, but are still in their infancy.
While
social big data is being proposed to fill some gaps and complement
traditional data types, several AI applications are also being proposed
to improve migration management. Some new approaches promise to
enable new migration-related indices, with better resolution in time
and space, as well as automated decision-making mechanisms for migration
management. Again, analysis is difficult, as big data and AI may suffer
from various biases and other problems. It remains to be seen how these
technologies will actually improve migration management, and whether
they will open new avenues for migration research.
In short, the use of AI and big data is a fundamental step for migration-related research,
and yet their combination is very recent. Methodologically, a holistic
approach is only possible by connecting the relevant international
research infrastructures, different disciplines, civil society
organisations and industry at national and international levels.
Teacher / speaker
Tuba Bircan
Prof. Tuba Bircan is a research professor of sociology at the Dept. of Sociology, at the Vrije Universiteit (VUB) and a senior researcher at the Kavli Research Centre for Ethics, Science and the Public at the
University of Cambridge. As a computational social scientist, her research interests cover a wide range from public perception, migration, equal opportunities, social and public policies to new methodologies
and use of Big Data and AI for studying societal challenges. She is a follower of open science and science for society. She is currently the scientific coordinator if H2020 funded HumMingBird-Enhanced Migration Measures from a Multidimensional Perspective project. She has published mainly on the methodological aspects of migration studies, inclusive policies and inequalities.
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