Incidente 667: translated-es-Manipulated Deepfake Video of Lai Ching-te Endorsing Rivals in Lead-up to January Presidential Elections
Descripción: translated-es-In the lead-up to Taiwan's presidential election in January 2024, a deepfake video circulated showing candidate Lai Ching-te endorsing his rivals. Taiwanese intelligence issued warnings of intensified Chinese disinformation campaigns, such as Spamouflage, aimed at manipulating the election outcome.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por People's Liberation Army , Chinese Communist Party , Base 311 y Unknown deepfake apps, perjudicó a Taiwanese voters , Lai Ching-te , Electoral integrity , Democratic Progressive Party y Democracy.
Sistema de IA presuntamente implicado: Unknown deepfake apps
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-At first, the short video of Lai Ching-te, one of Taiwan's three presidential election candidates, looks like any other campaign interview.
But on closer inspection, his speech is slightly stilted and his message -- endorsing …
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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