Excessive Automated Monitoring Alerts Ignored by Staff, Resulting in Private Data Theft of Seventy Million Target Customers

November 27, 2013

Automated monitoring alerts about a data breach at Minneapolis' Target were reportedly ignored due to the high volume of potential false alerts and some systems being turned off. This oversight led to the theft of private data for 70 million customers, highlighting the need for guardrails in AI governance and trustworthy 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 0.691, rank 1. TAIM detail and related incidents →
MEASURE 2.10 — similarity 0.690, rank 2. TAIM detail and related incidents →
MANAGE 4.1 — similarity 0.680, rank 3. TAIM detail and related incidents →

Alleged deployer: target
Alleged developer: fireeye
Alleged harmed parties: target, target-customers

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/193

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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