It's a bit different when "training on any data" means basically storing a lossily-compressed copy of that data, that could be spit out years later if the model decides to do so.
It's exactly the same problem as with humans, though.
It's part of why we sign NDAs, and why their duration is measured in years (and that's not even targeting the human retention - just duration after which information ages enough that its disclosure is not likely to negatively impact anyone who cares).
It's not exactly the same problem, in that you can parallelize usage of an LLM and copy it over to another computer, but cannot do the same things with a brain. Put it another way, humans do not have the processing power needed to answer hundreds of millions of queries per day, while LLMs do.
