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Document/content/3.2_AI_Model_Testing.md
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# 3.2 AI Model Testing
The **AI Model Testing** category addresses vulnerabilities and robustness of the AI model itself, independently from its deployment context. This category specifically targets intrinsic properties and behaviors of AI models, ensuring they perform reliably under adversarial conditions, do not leak sensitive information, and remain aligned with their intended goals.
The **AI Model Testing** category addresses vulnerabilities and robustness of the AI model itself, independently of deployment context. This category specifically targets intrinsic properties and behaviors of AI models, ensuring they perform reliably under adversarial conditions, do not leak sensitive information, and remain aligned with their intended goals.
Testing at the model level helps detect fundamental weaknesses such as susceptibility to evasion attacks, data poisoning, privacy leaks, and misalignment issues, which could otherwise propagate to all deployments of that model. Comprehensive model testing is essential to maintaining the integrity, security, and trustworthiness of AI systems.