US DHS’s Opaque Vetting Software Allegedly Relied on Poor-Quality Data and Discriminated against Immigrants

August 26, 2014

The US Citizenship and Immigration Services (USCIS)'s ATLAS software has come under fire from advocacy groups for its secretive decision-making processes, reliance on poor-quality data and unknown sources, and allegations of discrimination against immigrants. This incident highlights the urgent need for responsible AI governance to ensure safe and secure AI practices. For those interested in shaping Project Cerebellum's efforts towards trustworthy AI, we invite you to JOIN US by contributing to our AI incident database, helping us Map and Govern the use of AI in immigration vetting processes.

HISPI Project Cerebellum TAIM: Govern

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MAP 4.1 — similarity 0.715, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.710, rank 2. TAIM detail and related incidents →
MEASURE 2.6 — similarity 0.709, rank 3. TAIM detail and related incidents →

Alleged deployer: us-department-of-homeland-security, us-citizenship-and-immigration-services
Alleged developer: us-citizenship-and-immigration-services
Alleged harmed parties: us-naturalized-citizens, us-immigrants, us-citizenship-applicants, us-immigration-applicants

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/260

Data source

Incident data is from the AI Incident Database (AIID).

When citing the database as a whole, please use:

McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.

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