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Data-related (Insufficient quality control in data collection process)

Sub-category
Risk Domain

Vulnerabilities that can be exploited in AI systems, software development toolchains, and hardware, resulting in unauthorized access, data and privacy breaches, or system manipulation causing unsafe outputs or behavior.

"A lack of standardized methods and sufficient infrastructure, including the absence of quality control processes for collecting data, especially for high-stakes domains and benchmarks, can affect the quality and type of the data collected [173, 95]. This may include risks of dataset poisoning, inadvertent copyright violation, and test set leakages which invalidate performance metrics."(p. 12)

Other risks from Gipiškis2024 (144)