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Cisco's AI Report Warning: Inaccuracy is the Norm
23 May
Summary
- AI reports often contain inaccuracies and inconsistencies due to LLM limitations.
- Cisco recommends specific prompts and fixed sources for more reliable AI outputs.
- Starting fresh sessions is advised to prevent data cross-contamination in AI reports.
Companies exploring AI for security reporting should consider Cisco's findings on generating long-form content. Cisco warns that AI-driven reports frequently suffer from inaccuracies, unusual conclusions, and inconsistent styles, primarily due to the probabilistic nature of Large Language Models (LLMs).
These models predict text by selecting the next token, which can lead to variability. Cisco suggests improving AI report reliability by using granular, single-task prompts focused on specific content segments. Providing the AI with fixed source documents and clear formatting instructions is also recommended.
Researchers also highlighted a challenge where AI can cross-contaminate reports within a single session. To avoid this, Cisco advises starting a new, distinct session for every new incident report to ensure data integrity and prevent errors.
