machine-enabled artworks; Rule of origin; lemons problem; large language model; GPT
Abstract :
[en] In 2021, an artificial intelligence system wrote a law article. The results were far from perfect but begged the question of whether a human author will still be able to compete against artificial intelligence. Leaving aside the Luddites scenario, this paper starts with the premise that human-made art might be more valued than machine-enabled art. However, to be properly valued, machine-enabled and human-made art must be distinguishable—they are not. Indistinguishability creates an asymmetry in information. This leads to a ‘lemons problem’—that is, a market erosion of good-quality products (in this scenario, human-made products). Against that background, this paper proposes a solution in light of international law and rules of origin. This paper argues that the lemons problem induces the need for a rule of origin labelling work as either human-made or machine-enabled. Determining human or machine authorship may be dauntingly complex when the artwork owes its existence to both humans and machines. One solution may be to review how the country of origin is identified whenever products are not created in a single location and then to apply, mutatis mutandis, to rules of authorship origin the solutions once identified in the context of geographical origins, that is, the so-called ‘substantial transformation test’. In the context of machine-enabled artwork, this test is whether a human edited the machine output and, if so, whether those edits constituted a substantial transformation of the work of art.
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