概要: 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.
Alleged: Divyendra Singh Jadoun , Polymath Synthetic Media Solutions , Sagar Vishnoi , iToConnect , IndiaSpeaks Research Lab と Sumit Savara developed an AI system deployed by Bharatiya Janata Party (BJP) , Indian National Congress (INC) , Prem Singh Tamang , Y. S. Jagan Mohan Reddy と Ram Chandra Choudhary, which harmed Indian voters , General public misled by deepfake content , Political integrity and election fairness , Democracy と Truth.
インシデントのステータス
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
インシデントレポート
レポートタイムライン
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.
Wearing a cris…
バリアント
「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の 根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください
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