Migration Intelligence: AI and Bio-surveillance of Migration Flows
Giacomo Buoncompagni
Journal of Digital Information Management, Vol. 19, No. 2, 2021.
DOI: https://doi.org/10.6025/jdim/2021/19/2/59-64 
Link: https://www.dline.info/fpaper/jdim/v19i2/jdimv19i2_3.pdf
Abstract:
The Coronavirus pandemic has made the use of artificial intelligence even more pervasive. 

States have decided to initiate bio-surveillance, through automated drones and other types of technologies such as GPS in mobile phones, to track COVID-19 positive individuals through apps or smart thermal cameras to control the spread of the virus. The current health crisis is making us deal with the dilemma regarding 'invisible populations', and migrants in particular, which involves a number of social and technological problems. 

On the one hand, lack of visibility is a systematic aspect of population management that can benefit both governments and the people concerned. The illusion of a 'data panoptic' does not take into account the conditions under which data are collected, the gaps or limitations of an interoperable system: in any system, not everything is counted, and not in the same way. 

This invisibility can come in handy for shadowy economies and unscrupulous politicians ready to sound  Security alarms. On the flip side, for categories such as the homeless, prisoners, migrants and sex workers, invisibility can be a defence against attention that too often resembles control and surveillance. The technodigital management of migratory flows and migrants data clashes with ethical-legal issues that are still open, and which concern all those sectors that involve the massive use of technology. 

Issues that in this case have become the two big questions of the current research: does data monitoring risk becoming a control mechanism that hinders the recognition of fundamental human rights? Is it currently possible to predict the real risks and harms of the technologies used to digitally manage migration? 

The central thesis presented in this article aims to high as a result of neural network training actions) can significantly influence the management of migration flows in the (post)pandemic society. The methodology adopted is based on an in-depth study of legal, socio-political and technological academic literature and a comparison of different sources. It examines current trends in the development of digital tools and the consequences these may have for international migration and the individual lives of migrants in the host country. It is believed that this reflection, although mainly theoretical, can contribute to the debate on the future of digital management of international migration, inviting policy makers and experts in this field to reflect on the complexity of the relationship between AI and migrants, in order to develop an open, secure, ethical and shared data system as soon as possible. Furthermore, a new concept, called 'Migration Intelligence' will be introduced, and it is understood here as a set of specific activities concerning identity checks, border security and management, and analysis of biometric data on migrants, refugees and asylum seekers. and the consequences these may have for international migration and the individual lives of migrants in the host country. It is believed that this reflection, although mainly theoretical, can contribute to the debate on the future of digital management of international migration, inviting policy makers and experts in this field to reflect on the complexity of the relationship between AI and migrants, in order to develop an open, secure, ethical and shared data system as soon as possible. Furthermore, a new concept, called 'Migration Intelligence' will be introduced, and it is understood here as a set of specific activities concerning identity checks, border security and management, and analysis of biometric data on migrants, refugees and asylum seekers.