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Incident 1050: Reportedly AI-Generated Image Circulates Amid Reports of Tanzania Revenue Authority Job Interviews

Description: An image circulated on Facebook purporting to show hundreds of Tanzanians lining up for just five jobs at the Tanzania Revenue Authority (TRA). The photo, reportedly AI-generated, gained traction shortly after TRA invited over 100,000 applicants for interviews on March 29–30. Though TRA had announced more than 1,500 openings, the image misrepresented the situation, stoking public anxiety during a period of high unemployment.

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Alleged: Unknown AI image generator technology developer developed an AI system deployed by unknown, which harmed Tanzanian job seekers , Tanzania Revenue Authority (TRA) and General public in Tanzania.
Alleged implicated AI system: Unknown AI image generator

Incident Stats

Incident ID
1050
Report Count
1
Incident Date
2025-03-31
Editors
Daniel Atherton

Incident Reports

Reports Timeline

Incident OccurrenceAI-generated photo falsely shows hundreds lining up for ‘five jobs’ at Tanzania’s tax agency
AI-generated photo falsely shows hundreds lining up for ‘five jobs’ at Tanzania’s tax agency

AI-generated photo falsely shows hundreds lining up for ‘five jobs’ at Tanzania’s tax agency

africacheck.org

AI-generated photo falsely shows hundreds lining up for ‘five jobs’ at Tanzania’s tax agency
africacheck.org · 2025

IN SHORT: Some Facebook users claim that this photo shows hundreds of Tanzanians queuing for an interview at the Tanzania Revenue Authority, competing for just five jobs. While the country's unemployment crisis is real, this photo is not.

A…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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