This is how you create an ethical/responsible "ai" system that COMPENSATES contributors as long as their images are used...

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Basically -
(a) Opt-in/opt-out system. Contributors CHOOSE whether they want to participate. Works are added/removed from the training set, depending on the setting.
(b) For a 'fair' system (where you'd most likely get contributors WANTING to participate) - contributors benefit for EVERY SINGLE "AI" IMAGE generated.

How do you do that? It's quite simple, really.
- When the neural networks are set up - the ID # of the images is recorded for the data inputted - i.e., a "data point".
- When a customer "generates" an "AI" image - it "pulls" from sometimes tens, or hundreds or thousands of "data points" to create that image. All the ID#'s of images used in composing that "AI image" is recorded.
- Each contributor - image ID - is given a fractional portion of that generated sale. Which, obviously adds up the more images created.

Doing it this way is certainly much more ethical, AND equitable/fair - and most likely you'd have people WANTING to make images when they know they will be compensated for, not with a tool that is designed to "replace" them.

It also CAN (and SHOULD be) done retroactively - and is very easy to do so.

Going forward it is also very easy to do so.

So for example, let's say:

a) A customer pays $50 for an "AI" tool, and makes 500 images. So each "image" is worth $0.10.
b) Let's say one of those random images "used" 100 contributor files to do so in their neural network.
c) Using the current arrangement (33%), payment would work out as follows. (As an aside, the % should be upped significantly for contributors, because once the tool is in place, adobe doesn't really have to do much 'maintenance'. The 'work' is image creation. I'd suggest a 90% contributor/10% split, or at least 80% contributor-20% adobe. But a different topic).

But for now - using the 33% idea... $0.067 to adobe, $0.033 to the "contributor pool" for the image created.
100 'images' used to create the "ai" image, so $0.033/100 = $0.0033/contributor.

Obviously, for a single image that is not much - BUT - it also obviously quickly adds up, as 1000's of images are created with the "AI" tools.

Certainly much fairer, and equitable.

And OPT-IN/OPT-OUT respected. if a contributor chose to "opt-out" - then their data points would ALSO BE REMOVED from the dataset for future "AI" image generation. "OPTING IN" is likewise very easy - it simply 're-adds' the datapoints to the training set for "ai" image generation.

Programatically VERY EASY to do - although it requires a bit of work to set up. And doing it this way more likely to have contributors WANTING to participate, as opposed to getting very upset/annoyed because it was simply "taken" from them.

THAT is much more along the lines of "responsible AI", with creators in mind at the "center". Not the "pay once to you, we benefit forever on your works" model which creates resentment, and actually discourages future image creation (which long term, will make a useless "AI" tool, as it quickly becomes outdated).

It also makes Adobe a HUGE amount of money going forward, with nice consistent revenue for very little effort or work, and happy contributors that benefit too.

 I really do not think any microstock agency has any real interest in cretaing a really "honest" or "fair" or "ethical" compensation system for AI training. They are just throwing these words around because they hope it will be a selling point for their AI product to customers, that's all. 

Also, I don't think you can pay contributors per individual image that was used to create an AI image, because this is not how it works. The AI does not for example  "use 100 contributor files to create an image so in their neural network". The AI uses ALL images for it's training and then it does not use individual images once it creates an AI image. It uses it's 'knowledge' of all images it has ever 'seen".
 So basically all 360+ Million images in Adobe's database are used whenever Firefly creates AI content. And even IF you wanted to compensate these contributors for each individual use (which Adobe has no interest in. They want to earn money through the usage of an AI and "replace" having to pay real humans after all. Otherwise there would be no profit in it for Adobe if they still had to pay us), so if you say each Ai image is "worth" $0.10 that would mean Adobe would have to divide this amount through the over 360 Million images in their database and that would come down to an amount that is so small that it would not even accumulate to a single cent in 100 years....
 And here you can get a pretty good idea of how "worthless" our images have become thanks to AI.

you're off by several orders of magnitude and show you haven't really studied how ai training works - there millions++ of datapoints (not '100 ') and the identity of the images used in training is lost in creation of the dataset as there is no longer a simple correspondence between initial pixels (24MP/image at minimum) and the resulting dataset.  so when an ai image is generated there's no way to trace back

dont know your programming bkgd, but the solution you present is enormously complicated

For simplicity - I phrased it that way, and used easy to understand numbers. I very much do know what I'm talking about, and yes - it is possible, actually quite simple to do.

Now it is true many programmers are lazy - and use existing algorithms, instead of "thinking" - but definitely very easy/doable. I'm not talking about corresponding "pixel images" - I'm talking about the "model/representation". It is very easy, and very possible to "trace back" source images - or more specifically "source data" that were used in composing an image.

You'd have to re-code a few things, and to do things retroactively - run it on previous data (compositions/queries) - but almost every single company (i.e., midjourney for example) tracks EXTENSIVELY with MASSIVE web logs/stats/etc. So very easy not only to process payments retroactively - but also going forward.

It is just a matter of doing it.