Description: A purported deepfake video reportedly portrayed Indian Finance Minister Nirmala Sitharaman as endorsing an investment scheme claiming Rs 22,000 (about $236 USD) could yield Rs 5.5 lakh (about $5,900 USD) in a week. PIB Fact Check publicly debunked the video on April 16, 2026, stating it was fake and AI-generated and warning that neither the Government of India nor the minister endorsed the scheme.
Entities
View all entitiesAlleged: Deepfake technology developers and Synthetic audio generation technology developers developed an AI system deployed by Scammers, which harmed Nirmala Sitharaman , General public , General public of India , Indian investors and Epistemic integrity.
Alleged implicated AI systems: 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
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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New Delhi, April 16: The government's fact-checking arm PIB Fact Check on Thursday debunked a viral video that falsely shows Finance Minister Nirmala Sitharaman endorsing a high-return investment scheme, warning citizens against falling for…
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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