It would be possible to use AI (or data mining) to create an index of reliability for identifiers that would be based solely on their participation and performance on iNat. The algorithm would gauge the members skill based on metrics including their performance (esp. accuracy) in identifying the particular taxon and include the geographical scope of their expertise area.
I’m a rank amateur with no training in biology, but my use of iNat is serious enough. I manage a rather bio-diverse preserve and am committed to doing so as intelligently as possible. As such, I’m deeply indebted to the experts who share their knowledge here, and I feel my photographs are real data – a date, a time, a location and a quality image that would otherwise not be recorded. The diligence level of an observer could also be measured using the same kind of metrics I mentioned for identifiers. I probably wouldn’t score too high as an identifier, but I’d like to think my observations would score better. A good observer rating would be likely to attract skilled identifiers.
One more thing - I do pay in a little annual contribution of iNat. I’d be willing to pay a modest subscriber fee, and perhaps that could help provide financial support to quality identifiers. Doing quality IDs is highly skilled work, and it’s valuable.