Description: During the 2024 Indian elections, politicians used AI-generated deepfakes to reach voters, who might be unaware they're interacting with digital clones. Providers like Divyendra Singh Jadoun of Polymath Synthetic Media Solutions created deepfakes for personalized messages. This practice, used by various political parties, is not truthful, as voters may be misled by AI-generated content posing as genuine interactions with political figures.
Entités
Voir toutes les entitésAlleged: Divyendra Singh Jadoun , Polymath Synthetic Media Solutions , Sagar Vishnoi , iToConnect , IndiaSpeaks Research Lab et Sumit Savara developed an AI system deployed by Bharatiya Janata Party (BJP) , Indian National Congress (INC) , Prem Singh Tamang , Y. S. Jagan Mohan Reddy et Ram Chandra Choudhary, which harmed Indian voters , General public misled by deepfake content , Political integrity and election fairness , Democracy et Truth.
Statistiques d'incidents
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
5.1. Overreliance and unsafe use
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.
- Human-Computer Interaction
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
Rapports d'incidents
Chronologie du rapport
translated-fr-On a stifling April afternoon in Ajmer, in the Indian state of Rajasthan, local politician Shakti Singh Rathore sat down in front of a greenscreen to shoot a short video. He looked nervous. It was his first time being cloned.
…Variantes
Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.
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