Description: According to Medius, Deepfake scams have targeted 53% of businesses in the U.S. and U.K., with 43% falling victim. Using AI to create realistic fake videos and audio of corporate executives, scammers have successfully stolen millions, including $25 million from British engineering group Arup.
Entities
View all entitiesAlleged: Unknown deepfake technology developers developed an AI system deployed by Unknown scammers and Unknown deepfake creators, which harmed American businesses , British businesses , Finance professionals , Employees and Arup.
Incident Stats
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.
- 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
- Just over half (53%) of businesses in the U.S. and U.K. have been targets of a financial scam powered by “deepfake” technology, with 43% falling victim to such attacks, according to a survey by finance software provider Medius.
- Of the 1,53…
As deepfake technology evolves, the variety and sophistication of phishing attacks continues to increase. Organizations may wonder how to protect against deepfake attacks that can lead to significant financial losses and reputational damage…
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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