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.
Entidades
Ver todas las entidadesAlleged: Unknown AI music company developed an AI system deployed by Michael Smith, which harmed Spotify , Music streaming services , Apple Music y Amazon Music.
Estadísticas de incidentes
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
Informes del Incidente
Cronología de Informes
Un productor musical fue arrestado el miércoles y acusado de múltiples delitos graves por supuestamente estafar más de 10 millones de dólares en regalías utilizando cientos de miles de canciones generadas por IA.
Se alega que Michael Smith,…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.
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