The DOI matches its Crossref record; 71 of the 77 references it cites were found in a registry or an index.
International migration management in the age of artificial intelligence
Open accessAbstract
Abstract Artificial intelligence (AI) has the potential to revolutionise the way states and international organisations seek to manage international migration. AI is gradually going to be used to perform tasks, including identity checks, border security and control, and analysis of data about visa and asylum applicants. To an extent, this is already a reality in some countries such as Canada, which uses algorithmic decision-making in immigration and asylum determination, and Germany, which has piloted projects using technologies such as face and dialect recognition for decision-making in asylum determination processes. The article’s central hypothesis is that AI technology can affect international migration management in three different dimensions: (1) by deepening the existing asymmetries between states on the international plane; (2) by modernising states’ and international organisations’ traditional practices; and (3) by reinforcing the contemporary calls for more evidence-based migration management and border security. The article examines each of these three hypotheses and reflects on the main challenges of using AI solutions for international migration management. It draws on legal, political and technology-facing academic literature, examining the current trends in technological developments and investigating the consequences that these can have for international migration. Most particularly, the article contributes to the current debate about the future of international migration management, informing policymakers in this area of growing importance and fast development.
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Cites
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,730
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 2×
“To date, no machine has passed the Turing test, and it thus remains to be seen whether one day a computer will be able to think like a human being (Turing 1950).”
BackgroundFloridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., et al. (2018) · Minds and Machines · doi:10.1007/s11023-018-9482-5 · Cited by 4,774 · cited 2×
“…costs, and build more effective systems for international migration management (Chui et al. 2018) is an attractive one, it is equally important that such tools are developed and deployed within ethical (Floridi et al. 2018) and legal frameworks, in particular IHRL (McGregor, Murray and Ng 2019).”
BackgroundThe Black Box Society: The Secret Algorithms That Control Money and Information
Pasquale, F. (2015) · doi:10.4159/harvard.9780674736061 · Cited by 3,796
(2018) · Cited by 3,510
How the machine “thinks”: Understanding opacity in machine learning algorithms
Burrell, J. (2016) · Big Data & Society · doi:10.1177/2053951715622512 · Cited by 3,196 · cited 5×
“It is well established that in principle, individuals enjoy the same rights online as they do offline, including the right to privacy or the respect for one’s private life (Human Rights Council 2012; UN General Assembly 2014; Human Rights Council 2016; Schmitt 2017).”
BackgroundMethodInfluentialDigital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide
Norris, P. (2001) · doi:10.1017/cbo9781139164887 · Cited by 2,921
Algorithms of Oppression: How Search Engines Reinforce Racism
Noble, S. U. (2020) · doi:10.2307/j.ctt1pwt9w5 · Cited by 2,709
Thinking critically about and researching algorithms
Kitchin, R. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1154087 · Cited by 1,471
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Jain, A. (2017) · Business Economics · doi:10.1057/s11369-017-0027-3 · Cited by 1,094
Tallinn Manual 2.0 on the International Law Applicable to Cyber Operations
Schmitt, M. N. (2017) · Cambridge University Press eBooks · doi:10.1017/9781316822524 · Cited by 977
Human Rights Obligations of Non-State Actors
Clapham, A. (2006) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199288465.001.0001 · Cited by 831
How AI can be a force for good
Taddeo, M., & Floridi, L. (2018) · Science · doi:10.1126/science.aat5991 · Cited by 760
Parkhurst, J. (2016) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · doi:10.4324/9781315675008 · Cited by 756
Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Flach, P. (2012) · doi:10.1017/cbo9780511973000 · Cited by 753
The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power
Sam, J. S. (2019) · Internet Histories · doi:10.1080/24701475.2019.1706138 · Cited by 751
Artificial Intelligence and the ‘Good Society’: the US, EU, and UK approach
Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2017) · Science and Engineering Ethics · doi:10.1007/s11948-017-9901-7 · Cited by 733
The Internal Dynamics of Migration Processes: A Theoretical Inquiry
de Haas, H. (2010) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2010.489361 · Cited by 684
Castles, S. (2004) · Ethnic and Racial Studies · doi:10.1080/0141987042000177306 · Cited by 682
Aspiration, desire and drivers of migration
Carling, J., & Collins, F. L. (2017) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2017.1384134 · Cited by 623
The Rights of Refugees under International Law
Hathaway, J. C. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511614859 · Cited by 600
There is a blind spot in AI research
Crawford, K., & Calo, R. (2016) · Nature · doi:10.1038/538311a · Cited by 580
Quantifying Global International Migration Flows
Abel, G. J., & Sander, N. (2014) · Science · doi:10.1126/science.1248676 · Cited by 565
The Politics of Evidence-Based Policy Making
Cairney, P. (2016) · Palgrave Macmillan UK eBooks · doi:10.1057/978-1-137-51781-4 · Cited by 529
(2014) · Digital Commons at University of Maryland Carey Law (University of Maryland Francis King Carey School of Law) · Cited by 524
Singer, P. W., & Friedman, A. (2014) · doi:10.1093/wentk/9780199918096.001.0001 · Cited by 511
A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI
Wachter, S., & Mittelstadt, B. (2018) · doi:10.31228/osf.io/mu2kf · Cited by 463
The Factors that Make and Unmake Migration Policies
Castles, S. (2004) · International Migration Review · doi:10.1111/j.1747-7379.2004.tb00222.x · Cited by 461
The Politics of International Migration Management
Geiger, M., & Pécoud, A. (2010) · Palgrave Macmillan UK eBooks · doi:10.1057/9780230294882 · Cited by 398
Improving refugee integration through data-driven algorithmic assignment
Bansak, K. C., Ferwerda, J., Hainmueller, J., Dillon, A., Hangartner, D., Lawrence, D., & Weinstein, J. M. (2018) · Science · doi:10.1126/science.aao4408 · Cited by 371
Betts, A. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199600458.001.0001 · Cited by 335
Business and Human Rights: The Evolving International Agenda
Ruggie, J. G. (2007) · American Journal of International Law · doi:10.1017/s0002930000037738 · Cited by 282
(2007) · Digital Commons at University of Maryland Carey Law (University of Maryland Francis King Carey School of Law) · Cited by 277
The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement
Ferguson, A. G. (2020) · doi:10.2307/j.ctt1pwtb27 · Cited by 266
Ashutosh, I., & Mountz, A. (2011) · Citizenship Studies · doi:10.1080/13621025.2011.534914 · Cited by 242
Understanding the promises and premises of online health platforms
van Dijck, J., & Poell, T. (2016) · Big Data & Society · doi:10.1177/2053951716654173 · Cited by 232
Liability for damages caused by artificial intelligence
Čerka, P., Grigienė, J., & Sirbikytė, G. (2015) · Computer law & security review · doi:10.1016/j.clsr.2015.03.008 · Cited by 217
Non-Refoulement in a World of Cooperative DeterrencePreprint
Hathaway, J. C., & Gammeltoft‐Hansen, T. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2479511 · Cited by 216
What do we know about the International Organization for Migration?
Pécoud, A. (2017) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2017.1354028 · Cited by 209
INTERNATIONAL HUMAN RIGHTS LAW AS A FRAMEWORK FOR ALGORITHMIC ACCOUNTABILITY
McGregor, L., Murray, D., & Ng, V. (2019) · International and Comparative Law Quarterly · doi:10.1017/s0020589319000046 · Cited by 207 · cited 10×
“Identifying such gaps and acting on them would allow state authorities to prepare and adapt their reception conditions, thus complying with their legal obligations under international human rights law (IHRL).”
BackgroundInfluentialBias detectives: the researchers striving to make algorithms fair
Courtland, R. (2018) · Nature · doi:10.1038/d41586-018-05469-3 · Cited by 205
Artificial Intelligence Policy: A Primer and Roadmap
Calo, R. (2018) · University of Bologna Law Review · doi:10.6092/issn.2531-6133/8670 · Cited by 197
Lavenex, S. (2015) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2015.1102047 · Cited by 195
Are Current Tort Liability Doctrines Adequate for Addressing Injury Caused by AI?
(2019) · AMA Journal of Ethics · doi:10.1001/amajethics.2019.160 · Cited by 188
Complacency and Automation Bias in the Use of Imperfect Automation
Wickens, C. D., Clegg, B. A., Vieane, A. Z., & Sebok, A. L. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815581940 · Cited by 176
Critiquing Big Data: Politics, Ethics, Epistemology
Crawford, K., Miltner, K. M., & Gray, M. L. (2014) · Cited by 168
Seeking refuge in Europe: spaces of transit and the violence of migration management
de Vries, L. A., & Guild, E. (2019) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2018.1468308 · Cited by 153 · cited 1×
“Migration management is a contested notion (Ansems de Vries and Guild 2019).”
Non-Refoulement in a World of Cooperative Deterrence
Gammeltoft‐Hansen, T., & Hathaway, J. C. (2014) · eYLS (Yale Law School) · Cited by 144
Panizzon, M., & van Riemsdijk, M. (2018) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2018.1441600 · Cited by 143
The politics of evidence-based policy in Europe’s ‘migration crisis’
Baldwin‐Edwards, M., Blitz, B. K., & Crawley, H. (2018) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2018.1468307 · Cited by 123
Principles of Artificial Intelligence
(1980) · Elsevier eBooks · doi:10.1016/c2009-0-27546-5 · Cited by 114
Transformations in Network Governance: The Case of Migration Intermediaries
Groutsis, D. G., van den Broek, D., & HARVEY, W. (2015) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2014.1003803 · Cited by 97
Migration data using social media: a European perspective
Spyratos, S., Vespe, M., Natale, F., Weber, I. G., Zagheni, E., & Rango, M. (2018) · Joint Research Centre (European Commission) · doi:10.2760/964282 · Cited by 95
Introduction to Artificial Intelligence
Salvaris, M., Dean, D., & Tok, W. H. (2018) · Apress eBooks · doi:10.1007/978-1-4842-3679-6_1 · Cited by 81
Molnar, P., & Gill, L. (2018) · TSpace (University of Toronto) · Cited by 81
M. D. Anderson Breaks With IBM Watson, Raising Questions About Artificial Intelligence in Oncology
Schmidt, C. (2017) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/djx113 · Cited by 75
Harrison, J. (2013) · Impact Assessment and Project Appraisal · doi:10.1080/14615517.2013.774718 · Cited by 57
The Reality of the United Nations Guiding Principles on Business and Human Rights
Addo, M. K. (2014) · Human Rights Law Review · doi:10.1093/hrlr/ngt041 · Cited by 54
Crépeau, F., & Atak, I. (2016) · Netherlands Quarterly of Human Rights · doi:10.1177/016934411603400203 · Cited by 47
Crawley, H., & Blitz, B. K. (2018) · Journal of Ethnic and Migration Studies · doi:10.1080/1369183x.2018.1468393 · Cited by 43
Mobility, Development, Protection, EU-Integration! The IOM’s National Migration Strategy for Albania
Geiger, M. (2010) · Palgrave Macmillan UK eBooks · doi:10.1057/9780230294882_7 · Cited by 41
The Datafication of Mobility and Migration Management
Broeders, D., & Dijstelbloem, H. (2015) · Routledge eBooks · doi:10.4324/9781315756400-13 · Cited by 38
Beduschi, A. (2018) · Open Research Exeter (University of Exeter) · Cited by 36
Self-citationDijstelbloem, H. (2017) · Nature · doi:10.1038/543032a · Cited by 31
Language Analysis for the Determination of Origin
(2018) · Language policy · doi:10.1007/978-3-319-79003-9 · Cited by 29
Paradigm and Paradox of the Migration-Development Nexus: The New Border for North-South DialoguePreprint
Chetail, V. (2009) · SSRN Electronic Journal · Cited by 27
TRADE-OFFS BETWEEN EPISTEMIC AND MORAL VALUES IN EVIDENCE-BASED POLICY
Khosrowi, D. (2018) · Economics and Philosophy · doi:10.1017/s0266267118000159 · Cited by 25
Fear and international law-making: An exploratory inquiry
Bianchi, A., & Saab, A. (2019) · Leiden Journal of International Law · doi:10.1017/s0922156519000177 · Cited by 17
Migration and Asylum Data for Policy-Making in the European Union – The Problem with NumbersPreprint
Singleton, A. (2016) · SSRN Electronic Journal · Cited by 17
Refugee Policy in Brazil (1995–2010): Achievements and Challenges
Moreira, J. B. (2017) · Refugee Survey Quarterly · doi:10.1093/rsq/hdx014 · Cited by 14
Varieties of Governance in China
Lu, J. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199378746.001.0001 · Cited by 13
Flagged first, then by citations
6 of the 77 references couldn’t be matched to a known paper.
Research works printed but not linked: 20
- Backer, 2018, Next Generation Law: Data-Driven Governance and Accountability Based Regulatory Systems in the West, and Social Credit Regimes in China, Southern California Interdisciplinary Law Journal, 28, 123
- Carammia, 2018, Can We Anticipate Future Migration Flows?
- Chui, 2018, Notes from the AI Frontier. Applying Artificial Intelligence for Social Good
- Connor, 2017, The Digital Footprint of Europe’s Refugees
- Eubanks, 2018, Automating Inequality
- Gelb, 2018, Technology, Migration and the 2030 Agenda for Sustainable Development
- 2017, Data Bulletin: Informing a Global Compact for Migration. Issue No 3
- 2018, Big Data and Migration
- 2019, Migration Data Portal
- 2019, China
- Moor, 2006, The Dartmouth College Artificial Intelligence Conference: The Next Fifty Years, AI Magazine AAAI, 27, 87
- 2017, The Digital Footprint of Europe’s Refugees
- Rango, 2015, How Big Data Can Help Migrants
- Richardson, 2019, Dirty Data Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice, New York University Law Review, 94, 192
- Tangermann, 2017, Documenting and Establishing Identity in the Migration Process. Challenges and Practices in the German Context
- 2012, Demystifying Big Data: A Practical Guide to Transforming the Business of Government
- 2018, Biometrics in the Humanitarian Sector
- Wachter, 2018, Counterafctual Explanations without Opening the Black Box: Automated Decisions and the GDPR, Harvard Journal of Law & Technology, 31, 842
- 2013, Human Rights Impact Assessments. A Review of the Literature, Differences with Other Forms of Assessments and Relevance for Development
- 2018, Technology Landscape for Digital Identification
Cited by
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Legal and human rights issues of AI: Gaps, challenges and vulnerabilities
Rodrigues, R. (2020) · Journal of Responsible Technology · doi:10.1016/j.jrt.2020.100005 · Cited by 494
Artificial intelligence and crime: A primer for criminologists
Hayward, K., & Maas, M. M. (2020) · Crime Media Culture An International Journal · doi:10.1177/1741659020917434 · Cited by 173
Harnessing the potential of artificial intelligence for humanitarian action: Opportunities and risks
Beduschi, A. (2022) · International Review of the Red Cross · doi:10.1017/s1816383122000261 · Cited by 98
Self-citationNalbandian, L. (2022) · Comparative Migration Studies · doi:10.1186/s40878-022-00305-0 · Cited by 70
Big data for whose sake? Governing migration through artificial intelligence
Bircan, T., & Korkmaz, E. E. (2021) · Humanities and Social Sciences Communications · doi:10.1057/s41599-021-00910-x · Cited by 53
Metadata
- Authors
- Beduschi, A.
- Affiliations
- University of Exeter (GB)
- Corresponding author
- Beduschi, Ana
- ORCID
- Beduschi, Ana
- Venue
- Migration Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-02-10
- Volume
- 9
- Issue
- 3
- Pages
- 576-596
- ISSN
- 2049-5838 (ISSN-L)
- 2049-5846
- OpenAlex
- W3005767652
- Cited by
- 141
- References
- 77
- Citations by year
- 2026: 32 · 2025: 31 · 2024: 20 · 2023: 24 · 2022: 17 · 2021: 13 · 2020: 4
- FWCI
- 19.40
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Migration Studies (publishedVersion, cc-by)
- Open Research Exeter (University of Exeter) (publishedVersion, cc-by)
- SSRN Electronic Journal (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Topics
- Social Sciences › Sociology and Political Science › Migration, Refugees, and Integration
- Social Sciences › Political Science and International Relations › Gender and Women's Rights
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence, international migration management, border security, asylum determination, algorithmic decision-making, identity verification, international organizations, face recognition, dialect identification
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