Incidente 302: translated-es-Students Allegedly Wrongfully Accused of Cheating via Medical School's Internal Software
Descripción: translated-es-Dartmouth's Geisel School of Medicine allegedly falsely accused students of cheating during remote exams using an internally built system which tracked student activity patterns without their knowledge on its learning management platform.
Entidades
Ver todas las entidadesAlleged: Geisel School of Medicine's Technology staff y Canvas developed an AI system deployed by Geisel School of Medicine, which harmed Sirey Zhang , Geisel School of Medicine's students , Geisel School of Medicine's professors y Geisel School of Medicine's accused students.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
5.1. Overreliance and unsafe use
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.
- Human-Computer Interaction
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
Post-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
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HANOVER, N.H. — Sirey Zhang, estudiante de primer año en la Escuela de Medicina Geisel de Dartmouth, estaba en sus vacaciones de primavera en marzo cuando recibió un correo electrónico de los administradores acusándolo de [hacer trampa] (ht…
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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