Propagating misconceptions / false beliefs
Generating or spreading false, low-quality, misleading, or inaccurate information that causes people to develop false or inaccurate perceptions and beliefs
ENTITY
2 - AI
INTENT
3 - Other
TIMING
2 - Post-deployment
Risk ID
mit1344
Domain lineage
3. Misinformation
3.1 > False or misleading information
Mitigation strategy
1. Prioritize and enforce rigorous data governance protocols to ensure all AI training data is of high quality, complete, and verifiable. This includes conducting regular data audits and deploying Retrieval-Augmented Generation (RAG) architectures to anchor generative models to verified, external knowledge bases, thereby reducing the incidence of factual "hallucinations." 2. Implement robust human-in-the-loop oversight mechanisms that require human review and validation of all high-risk AI-generated outputs before their dissemination. Concurrently, mandate the maintenance of comprehensive, immutable audit trails and system logs to ensure transparency, traceability, and accountability for all AI-driven decisions and content production. 3. Initiate sustained, multi-level digital literacy and cognitive resilience campaigns targeting both employees and end-users. These programs must educate stakeholders on how to identify AI-driven deception (e.g., deepfakes, sophisticated misinformation) and establish clear organizational protocols for cross-referencing and verifying information authenticity across multiple reputable sources.