[thr3000]

OK, it seems like a nitpick argument, but I'll refine my statement, even if doing so obfuscates it and does not change the conclusion.

The AI was trained to maximize profit, defined as net profit before lawsuits (NPBL) minus lawsuits. Obviously the null AI has a NPBL of zero, so it's eliminated from the start. We can expect NPBL to be primarily a function of userbase minus training costs. Within the training domain, maximizing the userbase and minimizing lawsuits are not in much conflict, so the loss function can target both. It seems to me that the additional training costs to minimize lawsuits (that is, holding userbase constant) pay off handsomely in terms of reduced liability. Therefore, the resulting AI is approximately the same as if it was trained primarily to minimize lawsuits.

[staunton]

> Within the training domain, maximizing the userbase and minimizing lawsuits are not in much conflict

Not at all obvious (and I'd naively think it's wrong).

[thr3000]

So you think it's more than "not much." How much exactly? A 10% increase in userbase at peak-lawsuit?

It's obviously a function of product design. If they made a celebrity fake nudes generator they might get more users. But within the confines of the product they're actually making, I doubt they could budge the userbase by more than a couple percent by risking more lawsuits.