Amazon's AI Cameras Incorrectly Penalized Delivery Drivers for Mistakes They Did Not Make

September 20, 2021

A recent incident involving Amazon's AI-driven performance evaluation system incorrectly penalized delivery drivers for errors they did not commit, potentially affecting their eligibility for bonuses and incentives. This underscores the importance of trustworthy AI and safe and secure AI practices. For those interested in shaping responsible AI governance and ensuring harm prevention through proper guardrails for AI, JOIN US.

This incident highlights the need to Govern and Map such systems within the context of the HISPI Project Cerebellum TAIM (Trusted AI Model) framework.

Matched TAIM controls

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

MEASURE 2.6 — similarity 0.743, rank 1. TAIM detail and related incidents →
MEASURE 4.2 — similarity 0.700, rank 2. TAIM detail and related incidents →
GOVERN 1.2 — similarity 0.686, rank 3. TAIM detail and related incidents →

Alleged deployer: amazon
Alleged developer: netradyne
Alleged harmed parties: amazon-delivery-drivers, amazon-workers

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/116

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.