LLM06:2023 - Overreliance on LLM-generated Content

Description

Overreliance on LLM-generated content can lead to the propagation of misleading or incorrect information, decreased human input in decision-making, and reduced critical thinking. Organizations and users may trust LLM-generated content without verification, leading to errors, miscommunications, or unintended consequences.

Common issues related to overreliance on LLM-generated content include:

• Accepting LLM-generated content as fact without verification.
• Assuming LLM-generated content is free from bias or misinformation.
• Relying on LLM-generated content for critical decisions without human input or oversight.

How to Prevent

To prevent issues related to overreliance on LLM-generated content, consider the following best practices:

• Encourage users to verify LLM-generated content and consult alternative sources before making decisions or accepting information as fact.
• Implement human oversight and review processes to ensure LLM-generated content is accurate, appropriate, and unbiased.
• Clearly communicate to users that LLM-generated content is machine-generated and may not be entirely reliable or accurate.
• Train users and stakeholders to recognize the limitations of LLM-generated content and to approach it with appropriate skepticism.
• Use LLM-generated content as a supplement to, rather than a replacement for, human expertise and input.

Example Attack Scenarios

Scenario #1: A news organization uses an LLM to generate articles on a variety of topics. The LLM generates an article containing false information that is published without verification. Readers trust the article, leading to the spread of misinformation.

Scenario #2: A company relies on an LLM to generate financial reports and analysis. The LLM generates a report containing incorrect financial data, which the company uses to make critical investment decisions. This results in significant financial losses due to the reliance on inaccurate LLM-generated content.