Descripción: An AI-generated deepfake of Suharto, the deceased Indonesian dictator, was generated and circulated by the Golkar Party ahead of the February 2024 Indonesian elections. This video, which aimed to influence voter perceptions by invoking Suharto's legacy, sought to manipulate public opinion and misused deceased individuals' likenesses for political gain. The incident is another example of political deepfakes creating convincing misinformation.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Golkar Party, perjudicó a Indonesian electorate , Electoral integrity y Democracy.
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
A once-feared army general, who ruled Indonesia with an iron fist for more than three decades, has a message for voters ahead of upcoming elections – from beyond the grave.
“I am Suharto, the second president of Indonesia,” the former gener…
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.
