0 / 0
Spreading disinformation risk for AI
Last updated: Dec 12, 2024
Spreading disinformation risk for AI
Misuse Icon representing misuse risks.
Risks associated with output
Misuse
New to generative AI

Description

Generative AI models might be used to intentionally 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.

Background image for risks associated with input
Example

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.

Generative AI search and answer
These answers are generated by a large language model in watsonx.ai based on content from the product documentation. Learn more