You can't audit an AI model the way you audit a binary

Open up an AI model and what's actually inside is a floating array of decimal points. No one can look at that and confirm it hasn't been tampered with, doesn't contain bias, or wasn't trained on poisoned data.

This video covers why that changes how you need to think about trusting a model:

• Compiled software binaries are deterministic. You can trace the exact logic that made a decision. AI models don't work that way.
• Unpicking why a model made a call is an extremely heavy lift, if it's possible at all
• Without that ability to inspect it, provenance and chain of custody become the thing you're actually trusting
• Treat AI models the way you'd treat any black box making decisions in your software stack: verify where it came from before you verify what it does

If you can't unpick the model itself, you have to be able to trust its origin.

See how Cloudsmith helps teams verify the provenance of everything they pull, including AI models: https://cloudsmith.com

#AISecurity #SoftwareSupplyChain #DevSecOps #Cloudsmith