As has been stated before, this issue’s been discussed quite a few times throughout the course of iNat’s existence, and as bouteloua quoted me earlier, any possible “expert” rating would be based on iNat activity, not external factors.
I think better onboarding (we’re just starting to draw up some ideas now, I know it’s been a long time coming), disincentivizing unwanted behavior (eg blind agreeing), allowing to filter by identifier (as @nathantaylor suggested, I know it’s been a long time request), and other fixes can solve or mitigate a lot of the issues raised here.
I can’t speak for everyone, of course, but here’s what I’ve heard from two top identifiers on iNat what I’ve met who each focus on one difficult taxonomic group:
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one expert has told me one motivation is that it’s an incredible way for them to practice and learn because they’re seeing photos of varying quality from all over the world of their taxon of interest.
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another told me they really just like helping people and if they can give their time and expertise in a way that helps people learn more about what they see, it makes them happy and they believe it’s just a good thing to do.
Some others who I’ve talked to are motivated by generating the data they want and they understand it often takes outreach, humility, and patience to teach and empower people to get that data, make the right observations, and identify taxa. I understand not everyone has the skills or resources for that, but it’s possible, and benefits many members of the community.
I’m not an expert by any means, but I’m pretty good with some bits of California flora and fauna, and I just want to help people who are curious about what they saw. Maybe they won’t misID a spider or a snake and kill it next time see it, or maybe they’ll just be able to point out a flower to a friend the next time they’re on a hike. Whether that observation ever gets to research grade is beyond my power, and it’s not something I care about. And if it sounds like I have no ego involved here, that’s not the case because I still feel quite a sting if an ID of mine is corrected. 
But that fades quickly, and it’s a chance to learn both about the taxon in question and how I can improve myself.
I can’t find the exact words above, but I feel like there might also be a misunderstanding about the computer vision training set. We now train on ranks higher than species, so please don’t feel obligated to ID to species for the model. From the blog post about our last model:
For the first three models, we only trained them to recognize species. For the last two models, we’ve been able to train with coarser taxonomic ranks. For example, if each species in a genus has 10 photos, that might not be enough data to justify training the model to recognize any of those species, but if there are 10 species in the genus, that’s 100 photos, so we can now train the model to recognize the genus, even if it can’t recognize individual species in that genus. This approach allows the model to make more accurate suggestions for photos of organisms that are difficult (or impossible) to identify to species but are easy to identify to a higher rank