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Critical infrastructure component failures when integrated with AI systems

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.

"When relying on GPAI in critical infrastructure, there may be common mode failures that begin with vulnerabilities or robustness issues in the underlying model architecture or training setup. These failures may happen accidentally (in edge-cases) or due to adversarial inputs to the AI systems [58]."(p. 46)

Supporting Evidence (1)

1.
"For example, a failure in the scheduling software of a chemical plant caused by an adversarial keyword can cause damage to physical property through halting critical processes (e.g., cooling, mixing of reactants)."(p. 46)

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