Translators who've been picking up after machine translation for the last decade will tell you that it is not, in fact, useful to them. They get paid half as much as before, but correcting the machine output is as much work as translating from scratch, and sometimes more, since the machine can give results that look good at first glance but are fundamentally incorrect.
I'm a translator, and that might be true for Google Translate, but not GPT-4. GPT-4 produces translations that are generally accurate, and when instructed to copyedit its own work, well-written. In most cases, all I need to do is fix the occasional error and do some light copyediting. This is much less work than translating from scratch and results in superior quality, since it combines my own skills with the AI's. It is also useful for researching equivalents to obscure terms across languages.
I don't know much about professional translating, but wouldn't you be able to track the error rate of the machine translation by looking at the number of corrections? And then translators could use this as leverage to negotiate better pay if it's obvious they need are translating from scratch in, say, 50% of cases anyway.
Pay isn't really decided by how much work you do or even completely by how much they need you to do it. What you're describing is a reason to ask for more but it's not leverage to make them give it to you.
I think of machine translation as a tool for people who are not translators, but admins, writers and so on, but need cheap translations that are good enough.
You can be attentive while not giving your 100% to the task.
For example while writing a piece of code you might know what you want to accomplish but you aren't straining your brain to type out the actual code.
So you type the name of the method and GitHub Copilot gives you an implementation of that method.
