You do gesture at it with “maximum amount of harm”, but the specific framing I don’t quite see expressed here is this:
While a blackmailer may be revealing something “true”, the net effect (even if not “maximized” by the blackmailer) is often disproportionate to what one might desire. To give an example, a blackmailer may threaten to reveal that their target has a non-standard sexual orientation. In many parts of the world, the harm caused by this is considerably greater than the (utilitarian) “optimal” amount—in this case, zero. This is a function of not only the blackmailer’s attempt at optimizing their long-term strategy, but also of how people/society react to certain kinds of information. Unfortunately this is mostly an object-level argument (that society reacts inappropriately in predictable ways to some things), but it seems relevant.
This brings up the question of what you’re trying to optimize for when teaching; in particular, which segment of the student population are you trying to best teach? If the median, then this strategy will, at best, be useless, at worst, actively harm their learning. If the top percentile, then it may very well produce better outcomes than a more straightforward approach. But it does seem to be the case that there’s a trade-off.
Grubhub also exclusively uses its own drivers. See my response to Said: https://www.lesswrong.com/posts/z9hqPS6NNdNYLYunT/minimize-use-of-standard-internet-food-delivery#XRNiX7GgZ7pF6HD5Y
Here is a neutral (from the perspective of potential competition) source, that quotes industry insiders: https://nypost.com/2016/02/06/tech-giants-start-getting-serious-about-food-delivery/
I agree that delivery services provide significant value to the consumer for the reasons you describe. I suspect that in the situation where a specific class of restaurant (pizza places) already have their own delivery network in place (fixed costs already paid, domain-specific efficiencies already captured), a bare-bones online order system could easily beat out a full-service middleman like UberEats or Grubhub.
In fact for some services it’s 30%: https://get.chownow.com/blog/restaurant-delivery-killing-restaurants
I only learned about this a few days ago, and (bizarrely) thought it was only UberEats that had such a high fee schedule.
I think there’s an important distinction between x-risks and most other things we consider to be tragedies of commons: the reward for “cooperating” against “defectors” in an x-risk scenario (putting in disproportionate effort/resources to solve the problem) is still massively positive, conditional on the effort succeeding (and in many calculations, prior to that conditional). In most central examples of tragedies of the commons, the payoff for being a “good actor” surrounded by bad actors is net-negative, even assuming the stewardship is successful.
The common thread is that there might be a free-rider problem in both cases, of course.