Descripción: OpenAI's AI-powered transcription tool Whisper, used to translate and transcribe audio content such as patient consultations with doctors, is advertised as having near “human level robustness and accuracy.” However, software engineers, developers and academic researchers have alleged that it is prone to making up chunks of text or even entire sentences and that some of the hallucinations can include racial commentary, violent rhetoric, and even imagined medical treatments.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por OpenAI, perjudicó a patients , Patients reliant on Whisper y Medical practitioners reliant on Whisper.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
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.
- AI system safety, failures, and limitations
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
Unintentional
Informes del Incidente
Cronología de Informes
SAN FRANCISCO (AP) --- El gigante tecnológico OpenAI ha promocionado su herramienta de transcripción impulsada por inteligencia artificial Whisper como una herramienta con una "solidez y precisión cercanas a las de los humanos".
Pero Whispe…
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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