CSETv1 分類法のクラス
分類法の詳細Incident Number
39
Notes (special interest intangible harm)
4.4 - Technically, misinformation was involved because the deepfakes portrayed Barack Obama saying things he never actually said. However, it did not result in or cause harm.
Special Interest Intangible Harm
no
GMF 分類法のクラス
分類法の詳細Known AI Goal Snippets
(Snippet Text: The researchers used 14 hours of Obama's weekly address videos to train a neural network. Once trained, their system was then able to take an audio clip from the former president, create mouth shapes that synced with the audio and then synthesize a realistic looking mouth that matched Obama's. , Related Classifications: Deepfake Video Generation)
CSETv0 分類法のクラス
分類法の詳細Problem Nature
Unknown/unclear
Physical System
Software only
Level of Autonomy
Unclear/unknown
Nature of End User
Amateur
Public Sector Deployment
No
Data Inputs
14 hours of footage from Obama's public statements and addresses (2017), Jordan Peele's voice and lip movements (2018)
Risk Subdomain
3.1. False or misleading information
Risk Domain
- Misinformation
Entity
Human
Timing
Pre-deployment
Intent
Intentional
インシデントレポート
レポートタイムライン

Photo: University of Washington.
Artificial intelligence software could generate highly realistic fake videos of former president Barack Obama using existing audio and video clips of him, a new study [PDF] finds.
Such work could one day hel…

The researchers used 14 hours of Obama's weekly address videos to train a neural network. Once trained, their system was then able to take an audio clip from the former president, create mouth shapes that synced with the audio and then synt…

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