Description: A 21-year-old man in Delhi was reportedly arrested for allegedly using AI morphing tools to create obscene images of his ex-girlfriend and distributing them through fake Instagram accounts. Police said he impersonated her, used real photos, and targeted her followers to harass and defame her after their breakup. The accused evaded detection by reportedly using multiple unverified Instagram handles.
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The OECD AI Incidents and Hazards Monitor (AIM) automatically collects and classifies AI-related incidents and hazards in real time from reputable news sources worldwide.
Entities
View all entitiesAlleged: Unspecified AI image manipulation developers developed an AI system deployed by Unnamed 21-year-old male suspect from Delhi, which harmed Unnamed ex-girlfriend of 21-year-old male suspect from Delhi.
Alleged implicated AI systems: Unspecified AI image manipulation tools and Instagram
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
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
Incident Reports
Reports Timeline
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The Delhi Police Tuesday arrested a 21-year-old man from the Palam village for allegedly stalking, defaming, and sexually harassing his ex-girlfriend by creating explicit images of her using AI tools. The accused allegedly disseminated the …
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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