Algorithmic Borders: A Theoretical Framework of Automated Decision-Making, Risk Scoring and Accountability in Migration Management
DOI:
https://doi.org/10.68854/grqhdk49Keywords:
algorithmic borders, automated decision-making, risk scoring, algorithmic accountability, migration governance, biometrics, border externalisation, African migrants, ECOWAS, contestabilityAbstract
States now manage much of migration through software. Visa applications are triaged by risk scores, asylum claims are tested against phone data and language-analysis tools, travellers pass through biometric gates, and movements are forecast from administrative, mobile and satellite data. Scholarship describes these digital borders in detail but lacks a common vocabulary for the decisions they make, and its accounts of accountability were built largely around citizens contesting domestic decisions rather than non-citizens screened across jurisdictions. This theoretical paper asks what changes, conceptually and politically, when migration decisions are partly delegated to automated systems, and why this matters for African migrants. Following a conceptual, non-empirical design, it synthesises 53 peer-reviewed articles published from 2023 to 2026, selected purposively against explicit criteria from three bodies of scholarship: critical studies of digital and datafied borders; legal and public-administration research on automated decision-making, automation bias and accountability; and African-centred work on biometric identification, border externalisation and regional free movement. Each source was verified against its Crossref record, screened for retractions and editorial notices, and coded through integrative conceptual synthesis for the decision function described, the actor holding formal authority and the remedy available to the affected person. The paper builds a sorting–predicting–verifying framework. Sorting assigns people to risk tiers and processing tracks; predicting estimates future conduct or flows; verifying tests identity and testimony against machine-readable traces. Each function relocates discretion from a visible officer to an opaque model and its data, while the migrant’s means of challenge remain built for human decisions. Five propositions follow: the reproduction of historical exclusion through nationality-weighted risk, the asymmetric distribution of error between origin and destination populations, the dissolution of accountability across vendors, agencies and states, the export of verification infrastructures to African states, and the conditions under which African regional systems could replicate or resist these patterns. The paper closes with a framework for contestable automated migration decisions built on notice, reasons, human review with real authority, error correction and shared liability, and urges ECOWAS, the African Union and national authorities to build these safeguards into their digital borders from the outset.
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