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Home/Risks/Gipiškis2024/Benchmarking (Guideline contamination)

Benchmarking (Guideline contamination)

Sub-category
Risk Domain

Inadequate regulatory frameworks and oversight mechanisms that fail to keep pace with AI development, leading to ineffective governance and the inability to manage AI risks appropriately.

"Guideline contamination refers to scenarios where instructions for the collec- tion, annotation, or use of the dataset are exposed to the model [170]. These instructions may contain explicit data-label pairs that can improve the model’s capabilities for the task."(p. 19)

Supporting Evidence (1)

1.
"For example, for text-based models, this can include prompts used to generate synthetic data, as well as instructions for evaluators on the coverage and method of their evaluations of the model."(p. 19)

Other risks from Gipiškis2024 (144)