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Models distracted by irrelevant context

Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems

Gipiškis et al. (2024)

Sub-category
Risk Domain

AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.

"Models can easily become distracted by irrelevant provided information (such as “context” in LLMs), leading to a significant decrease in their performance after introducing irrelevant information. This can happen with different prompting techniques, including chain-of-thought prompting [184]."(p. 28)

Other risks from Gipiškis et al. (2024) (144)