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3. Misinformation2 - Post-deployment

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

Source: MIT AI Risk Repositorymit263

ENTITY

2 - AI

INTENT

3 - Other

TIMING

2 - Post-deployment

Risk ID

mit263

Domain lineage

3. Misinformation

74 mapped risks

3.1 > False or misleading information

Mitigation strategy

1. Develop and enforce rigorous content filtering mechanisms, including fine-tuning models against established safety policies and integrating real-time fact-checking APIs to proactively restrict the generation of known false or misleading statements. 2. Implement robust provenance tracing technologies, such as digital watermarking or metadata embedding, to clearly label synthetic content and enable rapid identification of the source model responsible for the propagation of misinformation. 3. Mandate continuous adversarial testing (red-teaming) throughout the development lifecycle to proactively identify and mitigate novel jailbreaks, prompt injection vulnerabilities, and other vectors for the intentional or unintentional generation and spread of false beliefs.

ADDITIONAL EVIDENCE

Example: A synthetic video of a nuclear explosion prompting mass panic (Alba, 2023)*