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Spreading disinformation risk for AI

Spreading disinformation risk for AI

Risks associated with output
Misuse
Amplified

Description

The possibility that a model could be used to create misleading information to deceive or mislead a targeted audience.

Why is spreading disinformation a concern for foundation models?

Intentionally misleading people is unethical and can be illegal. A model that has this potential must be properly governed. Otherwise, business entities could face fines, reputational harms, and other legal consequences.

Background image for risks associated with input
Example

Generation of False Information

As per the 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 cited include robocall messages generated in a candidate’s voice instructing voters to cast ballots on the wrong date, synthesized audio recordings of a candidate confessing to a crime or expressing racist views, AI generated video footage showing a candidate giving a speech or interview they never gave, and fake images designed to look like local news reports, falsely claiming a candidate dropped out of the race.

Parent topic: AI risk atlas

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