From the course: Handling Sensitive Data with Cloud and Local AI
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Build a safety framework for responsible AI use
From the course: Handling Sensitive Data with Cloud and Local AI
Build a safety framework for responsible AI use
We're going to start laying out the foundation for an AI safety framework. And for this, I want you to navigate to the courses repo. And under the safety framework directory, you'll see questions. Now, I'm going to go ahead and fill some of these out. I want you to do so as well, but do not create a public fork of this. Either copy this into a Word document or clone this into a private repo repo so that you don't answer these questions publicly and make this information readily available. I'm going to answer just a few of these using the persona of a company that develops an AI-powered travel companion. So let's go ahead and get started with these. Here, I'm going to edit this, and I'm going to use a tool called WhisperFlow to voice type this. Sometimes I type, sometimes I voice type. For this kind of stuff, I find that it helps me sort of flow and put my thoughts into writing quicker. So, first question. Which business outcomes will the AI influence and what's the maximum acceptable…
Contents
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Privacy controls in popular AI assistants3m 9s
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(Locked)
Understanding AI and data safety1m 4s
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(Locked)
Build a safety framework for responsible AI use2m 23s
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(Locked)
Choosing an inference platform2m 7s
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(Locked)
Visualizing LLM risks: Create an interactive UI2m 21s
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(Locked)
Build it: Implementing the dual LLM pattern4m 34s
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