Incidente 287: translated-es-OpenAI’s GPT-3 Reported as Unviable in Medical Tasks by Healthcare Firm
Descripción: translated-es-The French digital care company, Nabla, in researching GPT-3’s capabilities for medical documentation, diagnosis support, and treatment recommendation, found its inconsistency and lack of scientific and medical expertise unviable and risky in healthcare applications. This incident has been downgraded to an issue as it does not meet current ingestion criteria.
Entidades
Ver todas las entidadesClasificaciones de la Taxonomía GMF
Detalles de la TaxonomíaKnown AI Goal Snippets
One or more snippets that justify the classification.
(Snippet Text: Our unique multidisciplinary team of doctors and machine learning engineers at Nabla had the chance to test this new model to tease apart what’s real and what’s hype by exploring different healthcare use cases., Related Classifications: Question Answering)
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
Pre-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
Los siguientes incidentes anteriores se han convertido a "problemas" luego de una actualización de definición de incidentes y criterios de ingestión.
21: Una prueba de Turing más dura expone la estupidez de los chatbots
Descripción: El Wino…
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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