Description: Scammers are using AI to impersonate small businesses by copying their videos, logos, and social media posts. They create fake listings and ads, diverting customers to cheap knockoffs or stealing their money. This has severely impacted businesses like Bee Cups, Darn Tough Vermont, and Cascade hummingbird feeders, leading to significant financial losses, negative reviews, and damaged reputations. Their deployment of AI makes it challenging for small businesses to combat these fraudulent activities.
Entities
View all entitiesAlleged: OpenAI and Unknown AI developers developed an AI system deployed by Unknown scammers, which harmed small businesses , Small business customers , Small business employees , Bee Cups , Darn Tough Vermont and Jim Carter.
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
Copycats are stepping up their attacks on small businesses.
Sellers of products including merino socks and hummingbird feeders say they have lost customers to online scammers who use the legitimate business owners' videos, logos and social…
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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