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Incident 422: Deepfake of FTX's Former CEO Posted on Twitter Aiming to Scam FTX Collapse Victims

Description: A visual and audio deepfake of former FTX CEO Sam Bankman-Fried was posted on Twitter to scam victims of the exchange's collapse by urging people to transfer funds into an anonymous cryptocurrency wallet.

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Alleged: unknown developed and deployed an AI system, which harmed victims of FTX's collapse and Twitter Users.

Incident Stats

Incident ID
422
Report Count
1
Incident Date
2022-11-22
Editors
Khoa Lam
Applied Taxonomies
GMF, MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

4.3. Fraud, scams, and targeted manipulation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Malicious Actors & Misuse

Entity

Which, if any, entity is presented as the main cause of the risk
 

Human

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Intentional

Incident Reports

Reports Timeline

+1
Sam Bankman-Fried deepfake aims to scam FTX collapse victims
Sam Bankman-Fried deepfake aims to scam FTX collapse victims

Sam Bankman-Fried deepfake aims to scam FTX collapse victims

blockchaintechnology-news.com

Sam Bankman-Fried deepfake aims to scam FTX collapse victims
blockchaintechnology-news.com · 2022

A deepfake of former FTX CEO Sam Bankman-Fried aims to scam victims of the exchange’s collapse.

FTX was the third-largest cryptocurrency exchange and Bankman-Fried was seen as the face of crypto in Washington. The exchange enjoyed many cele…

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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