Incidente 671: Numerosas falsificaciones políticas circulan en vísperas de las elecciones generales de Pakistán de 2024
Descripción: Durante las elecciones generales de Pakistán de 2024, circularon deepfakes generados por IA con motivaciones políticas. Estos deepfakes presentaban falsamente a figuras políticas en contextos engañosos, difundiendo desinformación y buscando influir en la percepción de los votantes y los resultados electorales.
Entidades
Ver todas las entidadesAlleged: Pakistani political parties , Misinformation networks y Unknown deepfake creator developed an AI system deployed by Pakistani political parties y Misinformation networks, which harmed Rana Atif , Raja Bashara , Naeem Haider Panjutha y Imran Khan.
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
Pakistan's general elections 2024 were held amid the absence of internet services and mobile phone signals sparking concerning statements from global institutions including the U.S., the UK, the European Union (EU), and Amnesty Internationa…
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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