machine learning software behaviour is unpredictable since the developer cannot control what the software learns from the data.
If you control the model, the data, the input, and the random, then the output will be the same every time.
What you don’t have are feature flags. If you tell your code monkey “This LLM is racist! Fix it!” they won't find a racist flag to set to false or if racist code to remove.
Training data that reflects racism, or whatever problem you don’t like, will spread to all the nodes in a way that keeps the code monkey from reaching in and tweaking it. That’s because this kind or programming isn’t optimized for manual tweaking. It’s optimized to reflect the training data. You fix it with better data.
If you don’t want your kids to swear, don’t swear in front of your kids.
Or you can teach it what swearing is and when it’s inappropriate. It still won’t show up as a feature flag. It’s just more data.
They can also massage your input and censor the output to attempt to sanitize. But once the problem behavior is learned it’s always there, waiting for a new way to sneak out.
