Descripción: Edmodo, an education technology provider, violated the Children's Online Privacy Protection Act Rule (COPPA Rule) by collecting and using children's personal data for advertising purposes without parental consent, according to the FTC. The company outsourced its compliance responsibilities to schools, thereby making them "solely" responsible for COPPA compliance without adequate disclosure. Edmodo is facing a proposed order prohibiting such practices, marking a precedent in the ed tech industry.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Edmodo, perjudicó a Children whose data was collected and used for advertising y Schools and teachers who were misinformed and burdened with COPPA compliance responsibilities without adequate disclosure.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
2.1. Compromise of privacy by obtaining, leaking or correctly inferring sensitive 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.
- Privacy & Security
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
La Comisión Federal de Comercio ha obtenido una orden contra el proveedor de tecnología educativa Edmodo por recopilar datos personales de niños sin obtener el consentimiento de sus padres y utilizar esos datos para publicidad, en violación…
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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