Description: A viral video purportedly manipulated by AI shows Kenyan journalist Jeff Koinange endorsing a mobile gambling app. The video was reportedly created using AI deepfake techniques, uses footage from a legitimate news broadcast, and artificially alters Koinange's voice and mouth movements. Neither Koinange nor Citizen TV has promoted the app, and no legitimate source hosts the video.
Entities
View all entitiesAlleged: Unknown deepfake technology developers developed an AI system deployed by Scammers impersonating Jeff Koinange and Unknown scammers, which harmed Jeff Koinange and General public of Kenya.
Alleged implicated AI systems: Unknown deepfake app and Facebook
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
4.3. Fraud, scams, and targeted manipulation
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.
- Malicious Actors & Misuse
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 SHORT: **A video posted on Facebook shows Kenyan journalist Jeff Koinange endorsing a mobile gambling app. But the video was created using artificial intelligence.
In a video posted on Facebook, Kenyan journalist Jeff Koinange appears …
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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