Smart Governance and Migration Policymaking via Digital Technology for Sustainable Development

A special issue of Social Sciences (ISSN 2076-0760). This special issue belongs to the section "International Migration".

Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 5494

Special Issue Editors


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Guest Editor
Department for E-Governance and Administration, Danube University Krems, 3500 Krems, Austria
Interests: data governance; evidence-based policymaking; computational social sciences
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
International Centre for Migration Policy Development (ICMPD), Gonzagagasse 1, 1010 Vienna, Austria
Interests: migration policy cycle; migration partnerships and dialogues; migration data harmonization

Special Issue Information

Dear Colleagues,

The phenomenon of migration as such is as old as humanity itself. That being said, migration has received a different connotation during the past few decades, especially as a consequence of the 2015 “migration crisis”. Migration dynamics in an individual state are significantly influenced by the dynamics—as well as by the regulatory and the cooperation parameters—of the environment in which it is embedded, e.g., the European Union. This includes national measures and policies that are in place in the existing legal frameworks, such as the European Union New Pact on Migration and Asylum. In addition, special political or social events, together with political and economic conditions, as well as the legal frameworks in third countries, also play a significant role. Against this background, effective measures can hardly be taken on an exclusively national level and within the boundaries of the individual state. Rather, international cooperation is needed to achieve these goals, both within the EU and with third countries outside the EU, addressed by regulatory policies. This circumstance is also expressed by migration taking the position of a major cross-cutting concern within the Global Compact for Migration, the Global Compact for Refugees, as well as the 2030 Agenda of Sustainable Development. It is exactly these cross-cutting aspects that increase the complexity of the phenomenon of migration to a new level, resulting in migration taking the form of a challenging subject.

Against this backdrop, establishing political control and cooperation for the purpose of achieving desired migration and asylum policy goals proves to be extremely complex. This concerns both the agreement on common goals among different actors at different levels, and the alignment of national policies towards global and European frameworks. The formulation of national goals, strategies, and measures, as well as coordination in the implementation and impact assessment of these measures at different political levels, prove to be equally complex. It is thus necessary to rethink policy actions towards smart migration and asylum governance at national, regional and international levels. 

Smart governance and policymaking refer to the use of digital technology to enable collaboration and participation in a transparent way that involves all relevant stakeholders. For example, smart governance can be applied to refer to the quadruple helix approach, involving science, citizens, as well as the public and economic sector. In this context, big data and associated analytical approaches have the potential to improve insights into the complexity of migration dynamics, and thus, allow for improved evidence-based decision-making. Simulations and computational models can also be used to model these dynamics in order to account for emergent complexity.

The topics relevant to this Special Issue comprise, but are not limited to:

  • The improvement of access to migration data by breaking up data silos;
  • Data integration and data fusion using semantics for handling spatiotemporal data;
  • Development and sustainability of skills and competencies for big data analysis in migration;
  • Digital Ethics in the context of data- and technology-driven migration research;
  • Normative and legal perspectives towards the regulation of big data usage in migration;
  • Governance of extraterritorial interventions via computational social science approaches to assess policy measures and migration dynamics;
  • Use of data science and big data in the migration policy cycle;
  • Unintended side-effects of policy interventions via data and digitalization;
  • Interactions between migration, asylum policy measures, and broader mobility dynamics;
  • Smart governance and migration policymaking via digital technology.

Prof. Dr. Thomas Lampoltshammer
Barbara Salcher
Guest Editors

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Keywords

  • data governance
  • evidence-based policymaking
  • computational social sciences
  • migration policy cycle
  • migration data harmonization

Published Papers (2 papers)

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Research

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13 pages, 431 KiB  
Article
Embedding Ethical Principles into AI Predictive Tools for Migration Management in Humanitarian Action
by Andrea Guillén and Emma Teodoro
Soc. Sci. 2023, 12(2), 53; https://doi.org/10.3390/socsci12020053 - 18 Jan 2023
Cited by 2 | Viewed by 2360
Abstract
AI predictive tools for migration management in the humanitarian field can significantly aid humanitarian actors in augmenting their decision-making capabilities and improving the lives and well-being of migrants. However, the use of AI predictive tools for migration management also poses several risks. Making [...] Read more.
AI predictive tools for migration management in the humanitarian field can significantly aid humanitarian actors in augmenting their decision-making capabilities and improving the lives and well-being of migrants. However, the use of AI predictive tools for migration management also poses several risks. Making humanitarian responses more effective using AI predictive tools cannot come at the expense of jeopardizing migrants’ rights, needs, and interests. Against this backdrop, embedding AI ethical principles into AI predictive tools for migration management becomes paramount. AI ethical principles must be imbued in the design, development, and deployment stages of these AI predictive tools to mitigate risks. Current guidelines to apply AI ethical frameworks contain high-level ethical principles which are not sufficiently specified for achievement. For AI ethical principles to have real impact, they must be translated into low-level technical and organizational measures to be adopted by those designing and developing AI tools. The context-specificity of AI tools implies that different contexts raise different ethical challenges to be considered. Therefore, the problem of how to operationalize AI ethical principles in AI predictive tools for migration management in the humanitarian field remains unresolved. To this end, eight ethical requirements are presented, with their corresponding safeguards to be implemented at the design and development stages of AI predictive tools for humanitarian action, with the aim of operationalizing AI ethical principles and mitigating the inherent risks. Full article
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Review

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32 pages, 2396 KiB  
Review
A Literature Review on the Usage of Agent-Based Modelling to Study Policies for Managing International Migration
by Gabriele De Luca, Thomas J. Lampoltshammer, Shahanaz Parven and Johannes Scholz
Soc. Sci. 2022, 11(8), 356; https://doi.org/10.3390/socsci11080356 - 09 Aug 2022
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Abstract
This literature review is dedicated to the subject of agent-based modelling for the system of international migration, and of the modelling of policies that are known to aid in its management. The reason for the selection of agent-based modelling as a framework for [...] Read more.
This literature review is dedicated to the subject of agent-based modelling for the system of international migration, and of the modelling of policies that are known to aid in its management. The reason for the selection of agent-based modelling as a framework for studying international migration is that the system of international migration presents the characteristics of a complex system: notably, its property of emergence, which therefore imposes the usage of a methodology for its modelling that is capable of reflecting its emergent traits. The policies that we study are those that intervene in the country of origin of emigrants and that are aimed at decreasing the aggregate volume of emigrants from that country. The reason for this choice is that policies in the countries of origin have become particularly attractive today, especially in European countries, under the assumption that it should be possible to prevent the migrants from reaching the point of destination of their journey if some kind of action is undertaken before the migrants arrive. We start by discussing the theoretical constraints that suggest how this approach may only partially be valid. Then, to assist the development of future agent-based models that study migration, we identify via topic mining the ten topics that are most commonly discussed in the literature on the application to the international migration of agent-based models; this lets us highlight the characteristics of an agent-based model that should be included when the research task relates to the usage of ABM to study international migration and its associated policies. Finally, we indicate why the existing literature on the modelling of international migration is missing a key aspect that is required to correctly model policies: the integration between agent-based approaches and systems dynamics. Full article
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