AI labs can hardly just throw random confidential data into the training and then hope it does not leak into the output of their model in an obvious way.
If that would be found it would destroy their main source of revenue, it could became a major national security or healthcare enforcement matter, and result in criminal investigations.
Labs at least must study prompts in an airgapped fashion. From there, consider how they could generate synthetic data to train another model. After, require trusted staff to do multiple levels of independent granular reviews of all fruits of the highest-value stolen inputs. (Or for model training data only, data never has to leave the airgap.)
Definitely risky, anyway. Surely some AI user has sent data, in confidential mode, with a unique shape they expect to be able to recognize if a later model recreated a facsimile even with heavy substitutions… but labs could bring risk of getting caught (over next few years) down quite low with extraordinarily ultraparanoid strategy. (But hopefully everybody is just behaving!)
They could run some sort of analysis to find high value input, such as proprietary technology, algorithms, or strategy.
Then they could group them together for one specific topic, and produce a report that analyzes if the information is plausible.
If so, they can have it send to staff for review, who could then create a test set that rewards the model for going into the direction of the proprietary solutions known to work.
I'm no expert, but at least something like that sounds plausible to me. I still very much doubt they are doing this.
They can use LLMs to launder confidential customer sessions into trainable data. Then they can claim that they don't train on "your data" without it being technically incorrect.
If I know for a fact that you're cheating on your wife, and someone else asks how I know that, then a third person chirping about your sketchy business dealings is entirely irrelevant to the question, no matter how much suspicion it might otherwise raise.