New Technologies, and especially the application of Artificial Intelligence and Big Data analysis, can be an ally for Latin America and the Caribbean countries that, with scarce resources, are facing the biggest migratory challenges in the region’s history.
Access to data and information about the characteristics, location, and perceptions of the migrant population and their host communities allows countries and migratory authorities to increase their ability to design informed and effective policies for integration.
Two Days to Dive into the Opportunities of AI, Big Data, and Migration
At the Inter-American Bank’s headquarters in Washington DC, we had the opportunity to spend two days together with the Immigration Policy Lab’s (IPL) team to dive into some of the most innovative initiatives to take advantage of the opportunities that new technologies provide to gather data on migrants and migration.
In this blog, we share 4 examples of how we can take advantage of this data to promote the integration of the migrant population.
IPL-12 Integration Index: Measuring Migrant Integration
The IPL has developed a standard measure of integration which is based on the degree to which immigrants have the knowledge and the capacity to achieve success in their host society. The goal was to have a useful measure of integration for policy makers and researchers, that is applicable over time and in different scenarios.
After a thorough research process which included the revision of more than 50 surveys and the evaluation of construct validity, the IPL’s team developed a 12-question and 24-question index, made up of six dimensions (i.e., psychological, economic, political, social, linguistic, and navigational) with two or four questions per dimension, respectively. These indices have already been used in a wide variety of countries and contexts, such as France, Lebanon, and Japan, among other countries.
Understanding the Impact of Cash Assistance on Migrants
An interesting case of the application of the IPL-12 index is Colombia. In 2019, IPL partnered with Mercy Corps to provide cash assistance to Venezuelan refugees in Colombia and evaluate its effect using a panel study design. The main objectives are to learn about the effects that cash has on onward migration and to better understand the economic and social well-being of Venezuelan refugees during the COVID-19 pandemic. The survey was carried out on a sample of 2,600 Venezuelan migrants in La Guajira, Cesar, and Antioquia, Colombia, from March to June 2020 in two phases.
First, the baseline survey gathered information on demographics and household characteristics, and then, the follow-up surveys (collected in 3, 6, and 9-month intervals) gathered information on migration, IPL-12 integration index, etc. The data was collected through WhatsApp, which offers several benefits for respondents and for the research team. The results of the analysis indicated that: the IPL-12 index decreased over the 9-month survey period, potentially due to implications of COVID-19 restricted movement policies, and the unemployment rates increased.
Using Data to Geographically Match Migrants with Better Employment Opportunities
GeoMatch is a software tool created by IPL that supports placement decision-makers by using historical data to generate personalized location recommendations for migrants. More specifically, IPL's Geomatch gathers historical data and uses it to train Machine Learning models to recognize patterns between refugees’ characteristics and their likelihood to find employment at every affiliate, then it transforms individual-level predictions to case-level predictions, and recommends a location to optimize employment, subject to constraints.
Currently, GeoMatch is in pilot development phases in the US, Canada, the Netherlands, Sweden, Norway, and Switzerland. In Canada, IPL is implementing a client-facing version (as opposed to a placement organization version) of GeoMatch designed for economic immigrants, where they enter their preferences and individual profile information.
Measuring Attitudes on Social Media
How can we use social media data to develop real-time measures of mass and elite attitudes and behaviors?
As of 2018, every member of Congress had an active Twitter account where they broadcast policy positions, interact with other elected officials, communicate directly with constituents, and increase media coverage to enhance messaging or policy agendas. In this context, IPL developed the Congressional Tweet Tracker, which uses Twitter data to track tweets about immigration in real time and by location (state, city, or party/chambers). It measures topics' salience, sentiment (pro or anti-immigration), and trends.
Citizen Perception Laboratory on Migration
Twitter can also be a source of information to understand the evolution of public perception at a regional level. The Citizen Perception Laboratory on Migration provides resources and information on public perceptions and migration and offers access to a dashboard on the conversation on migration in Latin America and the Caribbean.
The social media dashboard of the Citizen Perception Laboratory on Migration searches for all posts on migration and provides insight into the evolution and content of the conversation. This allows governments, academics, and policymakers to identify trends to make data-based decisions.