EU: Artificial intelligence: "forecasting and early warning tool for migration" and "data spaces in law enforcement"

Two studies contracted by the European Commission on potential applications of "artificial intelligence" in home affairs were recently published: one concerning "a forecasting and early warning tool for migration"; and the other on "technical requirements for data spaces in law enforcement".

The migration study, by the consulting firm Ecorys, says:

"The overall objective of this study was to analyse the feasibility of developing a forecasting and early warning tool based on AI technology (hereafter ‘AI-Tool’), which is capable of forecasting and assessing the direction and intensity of irregular migratory flows to and within the EU and to provide early warnings and forecasts on this basis both in the short term (1 to 4 weeks) and in the medium term (1 to 3 months). This AI-Tool should be able to provide reliable estimates to allow the European Commission and the EU Member States to inform their migration management activities, such as the planning and organisation of capacities and other border management aspects accordingly." (emphasis added)

See: Feasibility study on a forecasting and early warning tool for migration based on artificial intelligence technology (pdf)

The study was produced because of "the conviction that situational awareness in the field of migration needed to be enhanced, as this was one of the main lessons learned from the 2015 so-called migration crisis," according to the minutes (pdf) of a February meeting of the European Commission's Expert Group on Artificial Intelligence in the domain of Home Affairs.

The author of the second study, on "data spaces in law enforcement", is listed as being 'Michael John Flynn'. This document states:

"At the level of the European Commission there has been a realisation that the European Union needs to ensure its place, on the world stage, in the field of Artificial Intelligence (AI), in particular in Big Data analysis, deep learning and machine learning. Essentially, a greatly heightened ability to analyse large amounts of non-homogenous data using analytical tools. In the sphere of law enforcement, many Member States are pursuing this goal, with a specific focus on the creation of intelligence products to support their tasks. However, although there is a great willingness to share data, good practice and products, the feedback from the Member States is that there needs to be a common (data) framework to pursue this work. Without such a framework, the risks are localised fragmentation and also datasets that could be larger and more representative of the operational data which will ultimately be analysed by the tools created. In this study, we will explore the state of development, the issues identified, the technical opportunities and the key activities that must be coordinated to make the strategic concept become a reality." (emphasis added)

The minutes of the first Expert Group meeting in July 2020 note that "if eu-LISA and Europol are to be entrusted with the data spaces project, an amendment of their mandate would be needed, as well as enough funding." Proposed amendments to Europol's mandate would in fact provide the agency with the ability to process vast datasets for the purposes of developing and testing new algorithms.

See: Study on technical requirements for data spaces in law enforcement (February 2021, pdf)


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