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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
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
Sorted by citations
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
