Descripción: In a case of AI washing, the SEC charged two investment advisers, Delphia and Global Predictions, for falsely stating their use of artificial intelligence in their investment strategies between 2019 and 2023. Their misleading claims resulted in a settlement whereby the firms agreed to pay a total of $400,000 in penalties, highlighting the critical consequences of misrepresenting AI capabilities on investment decisions and trust.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Global Predictions Inc. y Delphia (USA) Inc., perjudicó a Investors.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
3.1. False or misleading information
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.
- Misinformation
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
Respuesta post-incidente de Securities and Exchange Commission
Washington D.C., March 18, 2024 --- The Securities and Exchange Commission today announced settled charges against two investment advisers, Delphia (USA) Inc. and Global Predictions Inc., for making false and misleading statements about the…
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.
