This feels like it ought to be a corollary to Goodhart's Law ("When a measure becomes a target, it ceases to be a good measure"), or perhaps a specialized application thereof.
So whether you have a recommendation system or a chronological feed or whatever other way you want to display info—there is always that implicit Goodhartish: measure → target → behavior change.
You can't escape it.
The only question is how you want to harness it—how you can bring out the best in people (with their consent ideally!) and mitigate the negative impacts of Goodharting.
(Shameless plug, I'm working on this, e.g. https://techpolicy.press/can-algorithmic-recommendation-syst... )
The size of transistors was a good target for a very long time, like 60 years.
The height of basketball players.
Muscle mass, profile, or volume.
The profit margins of a company.
Scores on a standardized math test.