| The trouble is there seems to be an entire continuum when it comes to degree of transformation. The compiler produces more or less a direct (logical) translation so it's clearly some sort of derivative. We go from C to machine code but the output still "means" the same thing as the input. (More precisely, it's approximately a mathematically transformed subset of the original input. Lots of information is removed, things are reorganized, and a bit of extraneous information gets added in the process.) For something notably more muddy than a compiler, consider This Waifu Does Not Exist. Any given output is (typically) nowhere near any particular input but you can often spot various strong resemblances. Alternatively, the implementation of sketch-rnn (https://magenta.tensorflow.org/sketch-rnn-demo) is quite different - it outputs pen strokes instead of pixels. Still, the legal questions remain the same. For a significantly muddier example, consider GPT-3. The outputs are (typically) not even remotely similar to anything that was input except in very broad strokes. Where does Copilot fall along this continuum? For even more confusion, consider running a New York Times article through Google Translate. Are you in the clear to publish that? I seriously doubt it. But what about running it through an ML algorithm that (attempts to) produce a very brief summary of it? Many such implementations exist in the real world today. Their output is nothing like the input - should it still fall under the copyright of the original? Finally, it's worth pointing out that for many of the above computerized tasks there are direct human equivalents. Art can be traced on a light table. A drawing can be produced that fuses the styles of two references. News articles can be manually translated or summarized. Again, my intention here isn't to argue a particular side. I'm just trying to make it clear how complicated this stuff is and the fact that we don't have clear legal answers for most of it yet. |