From the course: Securing the AI/ML Development Lifecycle: A Practical Guide to Secure AI Engineering
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Program-level standards
From the course: Securing the AI/ML Development Lifecycle: A Practical Guide to Secure AI Engineering
Program-level standards
- [Instructor] Now that we understand how AI-enabled applications make their way from idea to production, let's look in detail at how we can add security and resilience to those processes. Specifically, let's look at some of the standards, frameworks, tools and techniques that we can build into AI development that help ensure that the results we get from those processes have security built in. Earlier in this course, we made the point that the means determine the ends, meaning the processes that we follow to develop something, be it software, an AI model, or anything else, dictates the end result. Another way to view this is through the architectural maxim form follows function. This is the idea that the form something takes relates to its use. In practice, what this means is that the program you follow, i.e. the scaffolding you have around how you do what you do, matters. So useful tools in your arsenal are…
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