Page 27 - IJPS-11-6

International Journal of
Population Studies Migration data management insights

The integration of AI into migration management migration management systems is indeed compelling
has sparked significant debate among scholars and (Chui et al., 2018). The ethical deployment of AI in
experts (Derave et al., 2022; Vavoula, 2021), particularly migration management should prioritize transparency,
concerning the regulatory frameworks that govern its use accountability, and inclusivity to safeguard against
(Kaneti, 2023; Molnar, 2019). potential unintended consequences that may arise from
It is imperative that the development and implementation automated decision-making processes.
of technological tools, particularly AI systems, are 4.2. BD4M
conducted in accordance with ethical considerations that
respect human rights, promote fairness, and avoid biases The rise in global migration has made effective tracking
that may adversely affect vulnerable populations (Floridi and analysis of migration data increasingly vital, and the
et al., 2018). However, one of the primary criticisms is digital revolution offers new opportunities by providing
that current legislative measures are often inadequate timely, extensive, and diverse digital data sources that can
to address the complexities and ethical implications improve migrant population estimates, reveal migration
associated with AI technologies in sensitive areas such as intentions, and aid in studying integration and cultural
refugee assistance. There is frequently a lack of scrutiny or assimilation (Rampazzo et al., 2023). The BD4M initiative,
assessment regarding the implications for refugees, even led by the International Organization for Migration (IOM,
when new developments are integrated into existing legal 2021), seeks to advance migration research through ethical
instruments (Vavoula, 2021). and responsible use of innovative data, fostering cross-
sector collaboration among governments, international
While AI tools have the potential to enhance efficiency organizations, academia, and civil society to strengthen
and improve service delivery within refugee support evidence-based policymaking on migration trends and
frameworks, their implementation must be approached human mobility.
with caution (Forti, 2021). Collins (2023) critiques
the prevailing narratives that often separate academic Big data has become crucial in tackling modern
discourse from real-world applications, suggesting challenges, with AI and advanced analytics revolutionizing
instead that migration knowledge is actively involved data collection and processing. By leveraging these
in shaping governance strategies. This intertwining of technologies, sectors like social, economic, and
theory and practice raises significant questions about governmental can address current and future issues
the role of academia in informing policy decisions more effectively. Balancing innovation with ethical
and the potential consequences of such influence on considerations, societies can enhance decision-making to
marginalized populations. By recognizing that academic benefit both individuals and communities. By addressing
insights contribute to the operationalization of migration the large gaps in the quantity and quality of data collected by
policies, Collins calls for a more reflective approach to how traditional methods, big data sources can assist in updating
knowledge is generated and utilized within this field. internal migration statistics (IOM, 2018; Lai et al., 2019).
As a means of addressing current knowledge gaps, big data,
AI has the potential to enhance migration management defined as large, complex data from numerous sources, is
through tasks like border control and identity verification. regularly proposed as a solution (Franklinos et al., 2021).
However, its application raises significant concerns
regarding bias in data and the lack of transparency, which Big data technologies enable the integration of migration
can adversely affect vulnerable migrant populations (Forti, data with economic, demographic, and geospatial datasets,
2021). providing a comprehensive understanding of migration
drivers and aiding policy decisions. In addition, real-
Giguashvili (2023) argues that AI can collect and time monitoring through satellite imagery and geospatial
analyze large datasets far faster than humans but highlights analysis helps detect population movements, allowing
concerns over data quality, particularly regarding migrant swift responses to migration crises and ensuring the safety
privacy, algorithmic accountability, and fairness. To of affected communities.
fully grasp migration dynamics, the author emphasizes
integrating both quantitative and qualitative data, including 4.3. Facebook
academic research, enabling not only statistical insights Facebook can identify a self-declared migrant’s information,
but also a more nuanced understanding of the subject. including location and Internet Service provider, by
To summarize, the proposition that AI technology has tracking their Internet protocol address when they access
the potential to foster innovation, decrease operational the platform. This data allows Facebook to personalize
costs, and enhance the efficiency of international content, ads, and recommendations based on the user’s

Volume 11 Issue 6 (2025) 21 https://doi.org/10.36922/ijps.6846