概要: In the lead-up to India's 2024 general elections, AI technology was used to create deepfake videos of deceased politicians, such as M. Karunanidhi and J. Jayalalithaa, aiming to influence voter behavior and campaign strategies. These AI-generated appearances are contributing to the erosion of trust in democratic processes and media discourse.
Alleged: Muonium と The Indian Deepfaker developed an AI system deployed by Dravida Munnetra Kazhagam , DMK と Various Indian political parties, which harmed Indian electorate , Indian voters , Democracy , Electoral integrity , Media discourse , M. Karunanidhi と J. Jayalalithaa.
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
3.1. False or misleading information
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.
- Misinformation
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
Bengaluru, India -- On January 23, an icon of Indian cinema and politics, M Karunanidhi appeared before a live audience on a large projected screen, to congratulate his 82-year-old friend and fellow politician TR Baalu on the launch of his …
Bengaluru (India) (AFP) -- Death has not extinguished the decades-long rivalry between two Indian leaders: both have now seemingly risen from the grave, in digital form, to rally their supporters ahead of national elections.
Political parti…
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