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The U.S. government's CBP One mobile app, required for asylum seekers at the U.S.-Mexico border, has been reported to contain facial recognition technology that fails to accurately map the features of Black individuals. This technical failure prevents many Haitian and African asylum seekers from completing their applications, effectively barring them from seeking asylum. Advocates and nonprofits have documented widespread error messages and are forced to implement workarounds, such as using high-intensity lighting, to attempt to bypass the bias.
CBP One's facial recognition feature was reportedly disproportionately failing to detect faces of Black asylum seekers from Haiti and African countries, effectively blocking their asylum applications.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Accuracy and effectiveness of AI decisions and actions are dependent on group membership, where decisions in AI system design and biased training data lead to unequal outcomes, reduced benefits, increased effort, and alienation of users.
Also classified as
The technical failure results in systemic exclusion and unequal treatment of Black asylum seekers at the border based on race.
The facial recognition software suffers from severe technical limitations and fails to perform reliably under real-world conditions.
The facial recognition system performs with significantly lower accuracy for darker-skinned individuals, directly preventing them from completing their asylum applications.
AI system
Due to a decision or action made by an AI system
Unintentional
Due to an unexpected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The exclusion of Black asylum seekers was an unexpected and unintentional outcome of deploying the CBP One app's facial recognition system post-deployment.
Added categories peak at 3: Substantial (Psychological Harm, Inferred)
The deployment of the CBP One app with biased facial recognition software systematically excluded darker-skinned asylum seekers from processing. While it presents negligible kinetic or intelligence threats, it represents a substantial human rights and operational challenge at the sovereign border due to algorithmic discrimination.
The CBP One app acts as an assistant that facilitates asylum processing by collecting user data and scheduling appointments, but it does not make independent autonomous decisions or plan goals.
High Risk: The system is used in migration, asylum, and border control management, specifically involving biometric identification and facial recognition, which has significant implications for fundamental rights.
The app relies on facial recognition technology to map features and verify the identity of asylum seekers before they can submit their applications.
The reports provide consistent, detailed accounts from multiple independent non-profit organizations and legal advocates working directly with affected migrants at different border locations. The technical failure of the facial recognition software is clearly documented, along with its direct impact on Black asylum seekers.
None
Technology
Facial Recognition Bias
The algorithm fails to recognize and register darker skin tones.
Frequent App Glitches
The app frequently crashes and displays error messages during use.
Family Appointment Logic Flaws
The system splits families by failing to register children under six.
Data Inputs
Biometric Photo Requirements
Mandatory photo submission relies on biased facial recognition tech.
Poor Low-Light Image Input
The app requires high-quality photos that fail in poor lighting camps.
Biometric Data Mandate
Forcing sensitive biometric data input creates technical bottlenecks.
Human Factors
Lack of Smartphone Access
Migrants lack high-end phones or stable internet to run the app.
Language Barriers
App was initially only in English and Spanish, excluding others.
Physical Accessibility Issues
Users with cataracts or poor eyesight struggle to use the interface.
Process and Methods
Mandatory App Usage Policy
DHS made the app the exclusive pathway for seeking asylum.
Lack of Pre-Rollout Testing
The application was not sufficiently tested for glitches before rollout.
No Alternative Process
Lack of offline or non-app alternatives for border processing.
Management
Failure to Consult NGOs
DHS did not consult civil society groups before the app rollout.
Inadequate Risk Assessment
Management failed to address known facial recognition demographic bias.
Poor Support Mechanisms
No assistance provided to migrants facing technical app rejections.
Regulatory Environment
Title 42 Restrictions
Strict border policies forced reliance on automated screening apps.
Lack of Biometric Regulations
Absence of laws banning or restricting biased biometric technologies.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
