Automation of Academic Fraud
學術造假自動化
Operation & Monitoring
Risk Description
When fabricated research is submitted in volume through automation and some of it is published; due to unmitigated control gaps, subsequent studies cite this content in their analyses, propagating errors layer by layer, and a substantial body of published literature remains affected even after retractions, triggering compliance exposure and operational reputational costs.
Framework Mappings
NIST AI 600-1Information Integrity
EU AI ActArt.50
NIST AI RMFMANAGE 2.4
ISO/IEC 5338運作與監控
MIT AI Risk RepositoryDomain 3
Risk Treatment & Implementation Guidance
Deploy AI-content detection to assist research-integrity review, identifying mass-submission patterns; Collaborate with publishing and research-integrity mechanisms on verification and retraction of suspect submissions; Monitor citation networks for error propagation and track affected literature after retraction