Being able to take location into account would be really good - earlier today, I am in Montreal, the AI’s third suggestion for a caterpillar was a New Zealand species !!
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It does on the web, and in the android app: each suggestion has either just “visually similar” or “visually similar / seen nearby” in green text under the italicized taxonomy name. The ones with “seen nearby” would fit location.
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I appreciate your clarification of the purpose of iNat. I will indeed keep in mind misidentifications invalidate research and weaken the Global Biodiversity Information Facility. My understanding of the purpose of iNaturalist was surely misguided. In my defense, as I have never been regarded as a wilting lily elsewhere in my life, I am going to share the genesis of my most recent activity on iNat so those scientists, researchers and experts reading this thread may learn why citizen scientist-users may appear negligent and/or flippant in regard to the importance of accuracy (in initial identification) - which includes blindly accepting AI suggestions.
After years of posting to my iNat account infrequently I recently added an image of a grass spider. At the time my country was in a COVID-19 lockdown; while at home, I began creating a virtual Life List. I shared my experience on social media and was encouraged by the iNat Twitter team to share more of my images.
On Twitter, iNat is described in this way,
At iNaturalist you can record your observations from nature, learn about biodiversity, and connect with other naturalists. Get outside, then check it out!
On Instagram, the description of the platform is described like this:
On iNaturalist, you can share your observations of wild organisms, get ID help, and make your findings available for researchers!
On Facebook, the Company Overview of iNaturalist is detailed:
iNaturalist.org is a place where you can record and share your observations of plants and animals! Make observations, keep track of your life list, and explore what others are seeing in your own backyard or on the other side of the world.
For all intents and purposes, I honestly believed iNaturalist was a place where I should share my photographs, work with a community of encouraging naturalists to identify my observations and ultimately, through the process…create a virtual life list of all the species I have encountered.
The objective of iNaturalist is perhaps misrepresented to the general public. While the Getting Started page mentions the criteria required for an observation to become Research Grade, it does not warn potential contributors their errors (naive, AI-encouraged or brazenly disruptive) will invalidate research or decrease the credibility of an international facility.
Thank you to everyone for clarifying the importance of identification accuracy, AI-related issues and the international consequences of citizen scientists’ participation in scientific research. I’ve always taken my own observation IDs seriously, that is why I asked the myriad questions that garnered eventual frustration from one expert. I did not perceive it as a ‘scolding;’ when I wrote I was discouraged, I meant that my confidence in my own identification skills was shaken. And, I was reminded that not every Community member is a patient partner in helping users identify their observations. As an educator I encourage questions; I forget that many IDers are potentially scanning observations on phone screens and have neither the time nor patience to engage in meaningful conversation in a comment box. 
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It does, but it also shows random species. It is a photo of a Fieldfare and the AI is right to give it as first id, but what the heck with later suggestions? Why seen nerby are in the end of the list while Falkland species is the 2nd?
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Yes! This is what I discovered was happening to me. I had uploaded hundreds of images from 2005-2010 (before I used Lightroom). When I began uploading images that had been keyworded in Lr the iNat AI suggestions were odd. I uploaded a number of images of orange fungi and each one came up Orange. That is when I learned that entering my location, clearing the suggestion “Orange” and allowing the AI to re-run its suggestions…the new suggestions were spot-on or at least more accurate to my Location! As no orange trees grow in Pennsylvania, that was an easy error to spot. I began entering my location as soon as I bulk upload and now I can usually beat the AI-suggestions before they are too bizarre (based on previous keywording).
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You are not mistaken. Per iNat staff, iNat is meant to connect people with iNat first, and any scientific value is a “byproduct”:
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I agree the CV needs improvement. I was just pointing out that it doesn’t completely ignore location.
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You are not misguided about the purpose of iNaturalist. Keep in mind that the opinions of individual users on iNaturalist may not always be in line with the actual stated purposes of iNaturalist itself.
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It is. Keep believing it. (But that doesn’t mean every user on iNaturalist or this forum is encouraging. Some are not.)
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Because geography is not considered in determining what suggestions are made. The list of suggestions is based on perceived visual similarity. If it so happens that what the algorithm thinks is the most similar is also seen nearby then that label will be added.
But the list is generated and ranked based only on what it thinks are the most similar looking.
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You are absolutely right about the stated purpose of iNat. But if it is a sole purpose and the scientific data is a byproduct, there are always other “buts”… First one: if the communication with nature is the sole purpose, why iNat proudly shows every scientific paper that was based on iNat data? Second one: why it is connected to GBIF? Third one: do you think that qualified identifiers (researchers among them) spend enormous amount of time at identifying entirely for the purpose for nature communication? It is for the sake of data correctness and education. If the users are not particularly interested in any ofthese, the IDers get frustrated and some leave - who gains then? You can read more about what response from the users or which behaviour frustrates experts, in the response of Myelaphus in this thread: https://forum.inaturalist.org/t/roles-of-taxonomic-experts-on-inat/13363/3
And here is a new thread on the problems of iNat ‘byproduct’: https://forum.inaturalist.org/t/data-quality-of-observations-from-india-data-quality-rg-gbif-india/13388
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However grumbly I am about AI suggestions, I do not think it is a good idea. I myself use AI for time saving purposes in cases when there are correct suggestions (that I know definitely) in the AI,just to save time instead of printing. And limiting AI usage willnot help very much. Instead, I would think, that rules of usage/tutorials should be made so, that the most problematic parts discussed in the forum threads must be strongly highlighted and - the most important thing - the new users should go through an obligatory read of the rules/tutorials. What I mean, when a user registers first time, there is a banner not allowing to go into a full use without going into any action until the user have not read the rules/seen a tutorial. Definitely, many people will just skip them still, but some will read them.
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YES! I find this happens all too often. iNat autofills the species id based on my file label. Sometimes this leads to off the wall identifications. Granted it is my responsibility to correct the id, but when you’re uploading 50+ images, it is easy to overlook one that has autofilled, but incorrectly. Even if my image is labeled correctly, it will upload only a portion of the file name. For instance Large Lace-border (Scopula limboundata) is OFTEN auto-filled as Lace Border (Scopula ornata), a species found in Great Britain. I think ekmes makes a very good point that labeling an identification as “out of range” would be a great addition, perhaps even highlighted in red.
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Thank you, I also decided it at least takes visual similarity as a main thing and I never read before it takes the geography in account.
Because GBIF have decided to incorporate the data.
iNat cant force that decision on them, nor does it in any way change what the iNat team or community see as the vision and role of the site.
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The field “owners_identification_from_vision” will tell you if if the observer’s ID used CV, the field “vision” will tell you if any particular ID used CV.
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This is a result of a relatively new feature that’s separate from the computer vision (Original request, bug reports, feature request for improvement).
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Are you saying the dependence on Research Grade data by GBIF-informed researchers was forged after iNat was created - rather than, iNat was created to inform GBIF?
What I am saying is GBIF is an independent organization separate from iNaturalist and they make their own decisions about which datasets they will incorporate or ask/choose to use.
Inat was not founded for the purpose of populating GBIF.
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