Spreading disinformation risk for AI
Description
Using a model to create misleading or false information to deceive or influence a targeted audience.
Why is spreading disinformation a concern for foundation models?
Spreading disinformation might affect human's ability to make informed decisions. A model that has this potential must be properly governed. Otherwise, business entities might face fines, reputational harms, disruption to operations, and other legal consequences.
Generation of False Information
According to the cited news articles, generative AI poses a threat to democratic elections by making it easier for malicious actors to create and spread false content to sway election outcomes. The examples that are cited include:
- Robocall messages that are generated in a candidate’s voice instructed voters to cast ballots on the wrong date.
- Synthesized audio recordings of a candidate that confessed to a crime or expressing racist views.
- AI-generated video footage showed a candidate giving a speech or interview they never gave.
- Fake images that are designed to look like local news reports.
- Falsely claiming a candidate dropped out of the race.
Parent topic: AI risk atlas
We provide examples covered by the press to help explain many of the foundation models' risks. Many of these events covered by the press are either still evolving or have been resolved, and referencing them can help the reader understand the potential risks and work towards mitigations. Highlighting these examples are for illustrative purposes only.