Description: A purported deepfake video reportedly circulated online falsely depicting Elon Musk endorsing a nonexistent "17-hour" diabetes cure. The reported video promoted unverified health claims and appears to have been part of a scam ecosystem exploiting Musk's public credibility. Rapper Boosie Badazz reportedly encountered and amplified the video before its purported falsity was identified.
Entities
View all entitiesAlleged: Deepfake technology developers and Synthetic audio generation technology developers developed an AI system deployed by Scammers impersonating Elon Musk and Scammers, which harmed Social media users , People with diabetes , People seeking medical advice , General public , Epistemic integrity , Elon Musk and Boosie Badazz.
Alleged implicated AI systems: Social media platforms , Deepfake technology and Synthetic audio generation technology
Incident Stats
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
AI
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
Incident Reports
Reports Timeline
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In a bizarre twist, rapper Boosie Badazz fell for an AI-deepfake video of Elon Musk promoting a fake diabetes cure, showing both the dangers of AI technology and the pitfalls of misinformation. Learn why this scam caught attention, its risk…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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