It's a good mental exercise to go through. Does the behavior of a small handful of AND/OR-style logic gates constitute "inference" (like the simple circuitry in a hand tool)? What about hundreds? Millions? At some point in this exercise we will have built a ML model, so where do we draw the line?

My point was that it's a spectrum, and the law doesn't seem to give guidance on where to draw the line on that spectrum. The hand mixer was just a clearly absurd example on the far opposite end of it, to show its breadth.

So back to your question; some improvements in my mind might be:

(1) Don't phrase this as an AI topic at all. Make laws about the safety of automated systems of all kinds which have health & safety implications — we already have lots of laws for cars (whether AI driven or not), medical equipment, and yes, even kitchen appliances (: Then, the definition of "AI Model" is irrelevant.

(2) If we do want something specific to AI, then the definition should be more specific. The definition could involve it being a stochastic process (unlike much other software), having inner workings that are poorly understood even by experts (unlike much other software), and whose logic is developed statistically from training data rather than being hand-designed (unlike much other software (or kitchen appliances!)).

If there is a single mapping from each set of inputs to one set of outputs (and no variation), then no, it isn't inference.

If the user stops the process when they want (instead of the process self regulating), it's hard to argue the process is doing anything in isolation.

So by that logic, if we run a ML model with a consistent pseudorandom seed each time (so the output is deterministic), then it is not doing inference?