You will have to adjust for cognitive biases during the prediction of how soon this will become a problem and understand that it can be used retroactively. So how easy it is to actually influence you (buying a lawn mower vs getting you to engage with something in a specific way) and what the limiting factors actually are now (seeing how old much of the preceding research is). With automatically generated content, another major hurdle for usability has been falling.

To clear this up, this isnt the old approach of finding juicy details from your psychiatrists file to pressure you with. Its about learning your decision making process and finding holes in it. Its pattern and error detection and attacking/supporting your OODA-loop. What is interesting here isnt your personal shortcommings but information about how you think and what you value. And the less friction your reaction entails (you are trained to not waste money) and the less of an action you have to take (no buy button) the easier it is to go unnoticed. Especially if you are missing a review loop.

edit: The only new thing here is really you training something to attack you even better. You are creating a key to your brain and dont care who gets it. Its bad enough when metadata is used and logs of your earlier communication (like this) but a journaling AI is as bad as i can imagine. I am going to reference back to OP to what the requirements for use are for this.

edit1: If you are working on this, pls read up on Daniel Schmachtenbergers concept of Metacrisis as well as the third attractor. This can get dangerous fast and progress doesnt stop with i assume either market forces or technological availability determining the likely path forward. So that tech should better be non dystopian. I dont see any non-cooperative design not rushing us towards a great filter. It is not value neutral and a technological impact assessment is very much necessary.

Sorry for the late edits