I’d also think about iNat as not just a “go outside, take photos, and generate data” thing, but an opportunity to also look at it through the lens of a data user. See this discussion.
In addition to that, I notice a lot of teachers seem to just have their students take photos and use the computer vision suggestions wthout thinking about them. To me iNat (or Seek) is the perfect opportunity to introduce students to the biases and problems (as well as the benefits) of machine learning models, as their world will be increasingly reliant on them. Discuss why iNaturalist might suggest something that’s incorrect - what about the photo might trick it? What other factors should you keep in mind when getting information from a machine learning model? Even if they never want to step out into nature again, they’ll learn how to critically think about these things.