Descripción: Three reportedly fake journals published by Addleton Academic Publishers manipulated Scopus rankings by extensively cross-citing each other and using AI-generated papers filled with buzzwords. These journals, placed in the top 10 of Scopus's 2023 CiteScore philosophy list, featured fake authors, affiliations, and grant numbers. This manipulation pushed legitimate journals to lower tiers, affecting academic evaluations and awards.
Entidades
Ver todas las entidadesPresunto: un sistema de IA desarrollado e implementado por Fake publications , Auricle Global Society of Education and Research y Addleton Academic Publishers, perjudicó a University hiring committees , University faculty , Scopus , Academic journals y University job candidates.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
3.1. False or misleading information
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.
- Misinformation
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
Recently our philosophy faculty at Jagiellonian University in Kraków, like many institutions around the world, introduced a ranking of journals based on Elsevier's Scopus database to evaluate the research output of its employees for awards …
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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