MIT AI Risk Repository · Risk Category · 14.06.00

Security

Description

"Artificial intelligence comes with an intrinsic set of challenges that need to be considered when discussing trustworthiness, especially in the context of functional safety. AI models, especially those with higher complexities (such as neural networks), can exhibit specific weaknesses not found in other types of systems and must, therefore, be subjected to higher levels of scrutiny, especially when deployed in a safety-critical context"

From Sources of Risk of AI Systems (Steimers2022), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
Other
Intent
Other

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

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Other entries from Steimers2022