Yes, in general you can conclude that attribution is not a hard science, you attribute the best you can given available information. But even then there's painful gotchas as described in the article above.
The real problem I was aiming at is that it doesn't scale in the context of mass improvement of Wikipedia articles.
Say I'm an enthusiast regarding species of fly found in NorthEast America. There's thousands of species and we have thousands of Wikipedia stub articles lacking an image.
Next, I found a source containing said images and want to use them. One would now have to go through every single source image and do attribution to the best of our ability.
Is there a title? Mandatory to use. No title? Make up your own. Is a license included? If so, 3.0 or 4.0? Is the author mentioned? If yes, does the author want to be mentioned by their real name? Has the author included any other custom requests? You need to honor them. And so on.
It's incredible laboursome work if you take on the task of doing it properly. As a result, many may not bother to improve Wikipedia images on such scale.
Now imagine those images being CC0. You can skip every single step and be a 100 times more productive.
Blunt statement, but the most useful images licenses are "copyrighted" and "CC0". Any license "in between" is messy, not as permissive as you may think, and in many use cases (such as social media) their license terms are fully ignored anyway.
As someone who uses a lot of photographs in presentations, I try to attribute as best I can but it can't really be automated, a lot of information is frequently missing, and the attribution isn't directly connected to the photograph. So it mostly counts as a good faith effort but probably doesn't really serve the intended purpose.
The CC non-commercial variant is also very problematic. It's easy to understand why people use it. But it means that if you're being cautious, you mostly don't want to use an NC photo because most "interesting" uses aren't unambiguously non-commercial.
https://wiki.creativecommons.org/wiki/Best_practices_for_att...
Yes, in general you can conclude that attribution is not a hard science, you attribute the best you can given available information. But even then there's painful gotchas as described in the article above.
The real problem I was aiming at is that it doesn't scale in the context of mass improvement of Wikipedia articles.
Say I'm an enthusiast regarding species of fly found in NorthEast America. There's thousands of species and we have thousands of Wikipedia stub articles lacking an image.
Next, I found a source containing said images and want to use them. One would now have to go through every single source image and do attribution to the best of our ability.
Is there a title? Mandatory to use. No title? Make up your own. Is a license included? If so, 3.0 or 4.0? Is the author mentioned? If yes, does the author want to be mentioned by their real name? Has the author included any other custom requests? You need to honor them. And so on.
It's incredible laboursome work if you take on the task of doing it properly. As a result, many may not bother to improve Wikipedia images on such scale.
Now imagine those images being CC0. You can skip every single step and be a 100 times more productive.
Blunt statement, but the most useful images licenses are "copyrighted" and "CC0". Any license "in between" is messy, not as permissive as you may think, and in many use cases (such as social media) their license terms are fully ignored anyway.