Incidente 761: translated-es-TikTok AI System Used to Amplify Election Disinformation by Foreign Networks
Descripción: translated-es-AI-generated misinformation on TikTok, driven by foreign networks, has flooded the platform with false narratives about the 2024 U.S. presidential election. Thousands of videos spreading political lies were identified, potentially influencing millions of users. Despite TikTok’s efforts to remove these accounts, the AI-driven disinformation campaign continues to challenge the integrity of the election.
Entidades
Ver todas las entidadesAlleged: TikTok developed an AI system deployed by Unknown TiKTok users from China , Unknown TikTok users from Iran , Unknown TikTok users from Nigeria y Unknown TikTok users from Vietnam, which harmed American electorate , Electoral integrity , Democracy y General public.
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
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translated-es-Intelligence officials have warned that the 2024 presidential contest could face an unprecedented flood of fake news, fueled by AI, from foreign actors. A Journal analysis of videos on TikTok has found it's already happening. …
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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