Descripción: Axon Enterprise considered development of remotely operated drones capable of tasering at a target a short distance away as a defense mechanism for mass shootings, despite its internal AI ethics board’s previous objection and condemnation as dangerous and fantastical.
Entidades
Ver todas las entidadesAlleged: Axon Enterprise developed an AI system deployed by none, which harmed US schools y US students.
Clasificaciones de la Taxonomía GMF
Detalles de la TaxonomíaKnown AI Goal Snippets
One or more snippets that justify the classification.
(Snippet Text: The May 24 school shooting in Uvalde, Texas that killed 21 prompted an announcement by Axon last week that it was working on a drone that could be operated remotely by first responders to fire a taser at a target up to 12 metres away., Related Classifications: Autonomous Drones)
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.2. AI possessing dangerous capabilities
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
Human
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
Intentional
Informes del Incidente
Cronología de Informes
Puntos clave:
- La empresa sorprendió a su propia junta de ética al anunciar la propuesta de tener drones armados con Taser en las escuelas.
- El director ejecutivo dijo que estaba decepcionado de que los miembros de la junta renunciaran antes…
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.