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Incidente 80: AI mistakes referee’s bald head for football — hilarity ensued

Descripción: In a Scottish soccer match the AI-enabled ball-tracking camera used to livestream the game repeatedly tracked an official’s bald head as though it were the soccer ball.

Herramientas

Nuevo InformeNuevo InformeNueva RespuestaNueva RespuestaDescubrirDescubrirVer HistorialVer Historial

Entidades

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Alleged: unknown developed an AI system deployed by Inverness Caledonian Thistle Football Club, which harmed livestream viewers.

Estadísticas de incidentes

ID
80
Cantidad de informes
2
Fecha del Incidente
2020-10-24
Editores
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

Clasificaciones de la Taxonomía CSETv0

Detalles de la Taxonomía

Problem Nature

Indicates which, if any, of the following types of AI failure describe the incident: "Specification," i.e. the system's behavior did not align with the true intentions of its designer, operator, etc; "Robustness," i.e. the system operated unsafely because of features or changes in its environment, or in the inputs the system received; "Assurance," i.e. the system could not be adequately monitored or controlled during operation.
 

Robustness

Physical System

Where relevant, indicates whether the AI system(s) was embedded into or tightly associated with specific types of hardware.
 

Consumer device

Level of Autonomy

The degree to which the AI system(s) functions independently from human intervention. "High" means there is no human involved in the system action execution; "Medium" means the system generates a decision and a human oversees the resulting action; "low" means the system generates decision-support output and a human makes a decision and executes an action.
 

High

Nature of End User

"Expert" if users with special training or technical expertise were the ones meant to benefit from the AI system(s)’ operation; "Amateur" if the AI systems were primarily meant to benefit the general public or untrained users.
 

Amateur

Public Sector Deployment

"Yes" if the AI system(s) involved in the accident were being used by the public sector or for the administration of public goods (for example, public transportation). "No" if the system(s) were being used in the private sector or for commercial purposes (for example, a ride-sharing company), on the other.
 

No

Data Inputs

A brief description of the data that the AI system(s) used or were trained on.
 

video feed, pre-tagged soccer match imagery

Clasificaciones de la Taxonomía CSETv1

Detalles de la Taxonomía

Incident Number

The number of the incident in the AI Incident Database.
 

80

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

no

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2020

Date of Incident Month

The month in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the month, estimate. Otherwise, leave blank. Enter in the format of MM
 

10

Date of Incident Day

The day on which the incident occurred. If a precise date is unavailable, leave blank. Enter in the format of DD
 

24

Estimated Date

“Yes” if the data was estimated. “No” otherwise.
 

No

Clasificaciones de la Taxonomía MIT

Machine-Classified
Detalles de la Taxonomía

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.
 
  1. 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

Incident OccurrenceEl partido de fútbol se arruinó cuando la cámara controlada por IA confundió la cabeza calva del árbitro con la pelotaLa IA confunde la cabeza calva del árbitro con el fútbol: se produjo la hilaridad
El partido de fútbol se arruinó cuando la cámara controlada por IA confundió la cabeza calva del árbitro con la pelota

El partido de fútbol se arruinó cuando la cámara controlada por IA confundió la cabeza calva del árbitro con la pelota

sbnation.com

La IA confunde la cabeza calva del árbitro con el fútbol: se produjo la hilaridad

La IA confunde la cabeza calva del árbitro con el fútbol: se produjo la hilaridad

thenextweb.com

El partido de fútbol se arruinó cuando la cámara controlada por IA confundió la cabeza calva del árbitro con la pelota
sbnation.com · 2020
Traducido por IA

La tecnología en los deportes es algo hermoso, pero a veces incluso los mejores inventos pueden salir mal. Esto sucedió el fin de semana en un partido de fútbol en Escocia, cuando una cámara controlada por IA se confundió y pensó que la cab…

La IA confunde la cabeza calva del árbitro con el fútbol: se produjo la hilaridad
thenextweb.com · 2020
Traducido por IA

Las mejores ligas y equipos de fútbol de todo el mundo tienen equipos de televisión y servicios de transmisión a su disposición para transmitir partidos a los fanáticos de todo el mundo. Sin embargo, debido a la pandemia de coronavirus, los…

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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Incidentes Similares

Por similitud de texto

Did our AI mess up? Flag the unrelated incidents

Security Robot Drowns Itself in a Fountain

DC security robot quits job by drowning itself in a fountain

Jul 2017 · 30 informes
Biased Google Image Results

'Black teenagers' vs. 'white teenagers': Why Google's algorithm displays racist results

Mar 2016 · 18 informes
Game AI System Produces Imbalanced Game

6 goof-ups that show AI is still in its diapers

Jun 2016 · 11 informes

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