Description: Michael Smith was arrested for allegedly using AI-generated songs and fake streaming accounts to scam over $10 million in royalties from major music platforms. By creating hundreds of thousands of songs and employing bots to artificially inflate streams, Smith circumvented fraud detection systems. The scheme was exposed after suspicions arose regarding the rapid generation of music and streaming anomalies.
Entities
View all entitiesAlleged: Unknown AI music company developed an AI system deployed by Michael Smith, which harmed Spotify , Music streaming services , Apple Music and Amazon Music.
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
A music producer was arrested Wednesday and charged with multiple felonies for allegedly scamming more than $10 million in royalties using hundreds of thousands of AI-generated songs.
Michael Smith, 52, of Cornelius, N.C., is alleged to hav…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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