I think AI has no moral compass, and optimization algorithms tend to be able to find 'glitches' in the system where great reward can be reaped for little cost - like a neural net trained to play Mario Kart will eventually find all the places where it can glitch trough walls.

After all, its only goal is to minimize it cost function.

I think that behavior is often found in code generated by AI (and real devs as well) - it finds a fix for a bug by special casing that one buggy codepath, fixing the issue, while keeping the rest of the tests green - but it doesn't really ask the deep question of why that codepath was buggy in the first place (often it's not - something else is feeding it faulty inputs).

These agentic AI generated software projects tend to be full of these vestigial modules that the AI tried to implement, then disabled, unable to make it work, also quick and dirty fixes like reimplementing the same parsing code every time it needs it, etc.

An 'aligned' AI in my interpretation not only understands the task in the full extent, but understands what a safe and robust, and well-engineered implementation might look like. For however powerful it is, it refrains from using these hacky solutions, and would rather give up than resort to them.