Scammers Using AI to Impersonate Small Businesses
April 1, 2024
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Such cases underscore the importance of trustworthy AI, proper AI governance, and guardrails for AI to prevent harm and ensure responsible use.
Matched TAIM controls
Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls
- GOVERN 2.2 — similarity 0.632, rank 1. TAIM detail and related incidents →
- MAP 4.1 — similarity 0.626, rank 2. TAIM detail and related incidents →
- GOVERN 6.1 — similarity 0.621, rank 3. TAIM detail and related incidents →
- Alleged deployer
- unknown-scammers
- Alleged developer
- openai, unknown-ai-developers
- Alleged harmed parties
- small-businesses, small-business-customers, small-business-employees, bee-cups, darn-tough-vermont, jim-carter
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/706
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.