Description: A Turkish student in Isparta was arrested for using ChatGPT to cheat during the 2024 YKS university entrance exam. The student, identified as M.E.E., is alleged to have employed a sophisticated setup involving a router, mobile phone, earphone, and a button-shaped camera to transmit exam questions to ChatGPT and receive answers in real-time.
Entidades
Ver todas las entidadesAlleged: OpenAI developed an AI system deployed by Turkish student identified as MEE, which harmed students , Turkish YKS exam takers y Turkish educational institutions.
Estadísticas de incidentes
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
Informes del Incidente
Cronología de Informes
A Turkish student has been arrested for cheating in the first round of the Institutions of Higher Learning Examination (YKS) through a mechanism that involves use of ChatGPT, a generative artificial intelligence model that gets more success…

El sábado, la policía turca arrestó y detuvo a un futuro estudiante universitario acusado de desarrollar un elaborado plan para usar inteligencia artificial y dispositivos ocultos para ayudarlo a hacer trampa en un importante examen de ingr…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.
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