Description: An automated license plate reader (ALPR) camera misread a 7 as a 2 and incorrectly alerted the local police about a stolen Oldsmobile car, which was allegedly not able to be verified by an officer before a traffic stop was effected on a BMW in Kansas City suburb.
Entidades
Ver todas las entidadesAlleged: unknown developed an AI system deployed by Prairie Village Police Department, which harmed Mark Molner.
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

Con el uso del lector de matrículas (LPR) rápidamente [en expansión] (http://arstechnica.com/tech-policy/2012/09/your-car-tracked-the-rapid-rise-of-license-plate-readers/) en todo Estados Unidos, no sorprende que a veces los oficiales deten…

Los lectores automáticos de matrículas pueden escanear matrículas a una velocidad de una por segundo. A nivel nacional, [varios cientos de millones](https://www.techdirt.com/articles/20140312/12072426552/dhs-may-have-publicly-dumped-its-lic…
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.