Black Uber Eats Driver Allegedly Subjected to Excessive Photo Checks and Dismissed via FRT Results

April 1, 2021

A former Uber Eats driver filed a lawsuit against the company, claiming they wrongfully dismissed him due to repeated false mismatches of his verification selfies. The driver alleged that these errors were a result of excessive verification checks, potentially discriminatory in nature. This incident underscores the need for safe and secure AI practices.

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Matched TAIM controls

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

MEASURE 2.6 — similarity 0.666, rank 1. TAIM detail and related incidents →
MAP 1.6 — similarity 0.665, rank 2. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.661, rank 3. TAIM detail and related incidents →

Alleged deployer: uber-eats
Alleged developer: uber-eats
Alleged harmed parties: pa-edrissa-manjang, uber-eats-black-delivery-drivers

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/265

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.

Pre-print on arXiv · Database snapshots & citation guide

We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.