How does the chapter suggest implementing security-by-design principles in AI systems?

The chapter suggests implementing security-by-design principles in AI systems by embedding security from the inception of development. This includes threat modeling to identify risks early and ensuring explainability and transparency of models.

Security-by-design principles in AI systems involve integrating security considerations from the beginning of the development process. This approach includes conducting threat modeling to identify potential risks such as data leaks and adversarial attacks early in the development cycle. An example of this is adapting Microsoft's STRIDE framework for AI. Additionally, ensuring that AI models are explainable and transparent is crucial, which can be achieved using tools like SHAP and LIME. This not only helps in understanding model decisions but also aids in regulatory compliance, such as adhering to GDPR's requirements for the "right to explanation" in automated decisions.