In praise of authentication: the case of Article 50(2) EU AI Act, its rule of origin and exception for substantial alteration
Jerome De Cooman
On June 18, Jerome De Cooman presented his research on Generative Artificial Intelligence and its economic impact in the art market at Trinity College Dublin as part of the International Symposium on Generative AI: Exploring Regulatory Opportunities, Challenges and Dilemmas.
As an appetizer, here is his abstract.
Generative artificial intelligence (GenAI) systems generate artwork likely to be copyrightable if made by human. In lieu of discussing whether GenAI artworks should be copyrighted, or whether copyrighted artworks can be used as training data under the fair use doctrine (US) or the text-and-data mining exception (EU), two questions that have received a large attention in academic scholarship so far, this paper proposes to analyse the economic implications of GenAI in the art market. Although the valuation of their outputs is still mostly unknown, preliminary studies show that, all other things being equal, humans’ works are evaluated at a significant higher value than GenAI ones. Yet, to be properly valued, human-made and GenAI products must be distinguishable. They are not. This indistinguishability creates an asymmetry in information that in turn leads to a lemons problem, defined as a market erosion of good-quality products. Against that background, this paper draws a parallel, from an economic perspective, between human-made v. machine made artworks on the one hand, and genuine artworks v. forgeries on the other. In light of this, this paper analyses the effectiveness and limitations of the solution proposed by the EU legislature in Regulation 2024/1689 (AI Act), i.e., an authenticating rule mandating both providers and developers to ensure that GenAI’s outputs are marked in a machine-readable format and detectable as artificially generated, except if the system solely performs an assistive function for standard editing or does not substantially alter the input data provided by the deployer or the semantics thereof (art. 50(2) AI Act).
