Description: Russian operatives used AI to create a fake video and voice of "Olesya," a supposed troll in Kyiv, falsely claiming involvement in U.S. elections to support President Biden. U.S. intelligence confirmed the voice was AI-generated. This disinformation campaign aimed to mislead voters, erode trust in democratic institutions, and influence the 2024 election. The incident involved the group Storm-1516, individuals linked to Valery Korovin, and potential veterans of the Internet Research Agency.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Valery Korovin , Storm-1516 , Internet Research Agency veterans y Center for Geopolitical Expertise, perjudicó a Ukrainian general public , Joe Biden , General public , Democratic institutions , Biden presidential campaign y American conservatives.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
4.1. Disinformation, surveillance, and influence at scale
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
Last month, a video began circulating on social media purporting to tell the story of an internet troll farm in Kyiv targeting the American election.
Speaking in English with a Slavic accent, "Olesya" offers a first-person account of how sh…
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.
