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This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .

Benchmarking (Post-deployment contamination)

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

Gipiškis et al. (2024)

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.

"Once a model is deployed, it can be exposed to benchmark data provided by the users [95, 170]. The model may then be further trained by these user inputs containing benchmark data."(p. 19)

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