> The relevant part of the license is the definition of the covered work, which basically says that the output of any algorithm that uses copyrighted code as input is under the same license.
In other words, you are granting unnecessary additional permission to use the output of an ML algorithm trained on the copyrighted code under the terms of the same license, when your permission was not required if the use of that output was already covered by fair use. If the use is not considered fair use—if the output would be deemed a derivative work under copyright law—then this license is beneficial to the developers of ML systems like Copilot since it explicitly grants them permission to use the output under the same terms. In the best case it's fair use and your license is irrelevant, and in the worst case your license grants them a path to proceed anyway, with a few extra rules to follow. Under no circumstances can anything you write in the licence expand the reach of the copyright you have in the original code, no matter how "wonderfully broad and general" the license may be.
Reading through the licenses and FAQs on your site did not improve my opinion of them in the slightest. Especially the part where you attempted to equate what Copilot does with trivial processing of the source code, e.g. with an editor, to argue that classifying the use of any output from an ML algorithm trained on copyrighted inputs as fair use is equivalent to eliminating copyright on software. The reality is of course much more nuanced. Certainly if the ML algorithm merely reproduces a portion of its input from some identifiable source, including non-trivial creative elements to which copyright could reasonably be applied, then the fact that the process involved an ML algorithm does not preclude a claim of infringement, and it would be reasonable to apply something like a plagiarism checker to the ML output to protect the user from accidental copying. However, the purpose of an ML system like Copilot is synthesis, extracting common (and thus non-creative) elements from many sources and applying them in a new context, the same as any human programmer studying a variety of existing codebases and subsequently writing their own code. The reproduction of these common elements in the ML output can be fair use without impacting the copyrights on the original inputs.
The real question here is why I'm wasting my time attempting a good-faith debate with someone who thinks that "spreading FUD is not necessarily a bad thing…".