Diritto d’autore e intelligenza artificiale: ampio studio per il Parlamento Europeo

Approfondito studio di Nicola Lucchi per il Parlamento Europeo Generative AI and Copyright Training, Creation, Regulation, luglio 2025:

Riporto i cinque principali punti come riassunti nell’Execurtive Summary:

“This study identifies five key findings:
(1) The current EU text-and-data mining (TDM) exception was not designed to accommodate the expressive and synthetic nature of generative AI training, and its application to such systems risks distorting the purpose and limits of EU copyright exceptions.
(2) Fully machine-generated outputs should remain unprotected; AI-assisted works require harmonised protection criteria.
(3) A statutory remuneration scheme is essential to bridge the growing value gap between creators and AI developers.
(4) The fragmented governance landscape underscores the need for more coherent, cross-sector institutional responses.
(5) Without timely reform, the EU risks legal uncertainty, market concentration, and cultural homogenisation”.

(segnalazione di Martin Ebers in Linkedin)

Lo sviluppo dell’ A.I. generativa su materiali protetti da diritto d’autore ne comporta la violazione? Probabilmene si, secondo la 3° parte dello studio dell’ US Copyright Office

Dopo le parti 1 e 2,  è ora uscita la parte 3 dell’ampio studio dello US Copyright Office sul rapporto tra AI e diritto di autore (Copyright and Artificial Intelligence Part 3: Generative AI Training, May 2025).

La parte 3 (come anticipato nel mio post 28.02.2025  sulla parte 2) riguarda la questione del se lo sviluppo o in generale la preparazione  dell’AI su materiali protetti incida sui relativi diritti.

La risposta è positiva. Resta allora da capire -nel diritto USA- se sia invocabile la difesa del Fair Use: soluzione difficile, conclude l’Ufficio, per cui è auspicabile il diffondersi di un adeguato sistema di licenze.

La questione è più complicata nel diritto UE, dove manca una clausola generale permissiva di pari portata, essendovi invece eccezioni (o limitazioni) specificamente previste.

Ecco la Conclusione:

<<In applying current law, we conclude that several stages in the development of
generative AI involve using copyrighted works in ways that implicate the owners’ exclusive rights. The key question, as most commenters agreed, is whether those acts of prima facie infringement can be excused as fair use.
The fair use determination requires balancing multiple statutory factors in light of all relevant circumstances. Although it is not possible to prejudge the result in any particular case, precedent supports the following general observations:
Various uses of copyrighted works in AI training are likely to be transformative. The extent to which they are fair, however, will depend on what works were used, from what source, for what purpose, and with what controls on the outputs—all of which can affect the market. When a model is deployed for purposes such as analysis or research—the types of uses that are critical to international competitiveness—the outputs are unlikely to substitute for expressive works used in training. But making commercial use of vast troves of copyrighted works to produce expressive content that competes with them in existing markets, especially where this is accomplished through illegal access, goes beyond established fair use boundaries.
For those uses that may not qualify as fair, practical solutions are critical to support ongoing innovation. Licensing agreements for AI training, both individual and collective, are fast emerging in certain sectors, although their availability so far is inconsistent. Given the robust growth of voluntary licensing, as well as the lack of stakeholder support for any statutory change, the Office believes government intervention would be premature at this time.
Rather, licensing markets should continue to develop, extending early successes into more contexts as soon as possible. In those areas where remaining gaps are unlikely to be filled, alternative approaches such as extended collective licensing should be considered to address any market failure.
In our view, American leadership in the AI space would best be furthered by supporting both of these world-class industries that contribute so much to our economic and cultural advancement. Effective licensing options can ensure that innovation continues to advance without undermining intellectual property rights. These groundbreaking technologies should benefit both the innovators who design them and the creators whose content fuels them, as well as the general public.
Finally, as in prior Parts of this Report, the Office recognizes that facts on the ground are evolving at a rapid pace. We will continue to monitor developments in technology, case law, and markets, and to offer further assistance to Congress as it considers these issues >>

L’intelligenza artificiale di Facebook viola il diritto di elaborazione delle opere letterarie utilizzate?

Large Language Model Meta AI (LLaMA)  (v.ne la descrizione nel sito di Meta) non viola il diritto di elaborazione sulle opere letterarie usate per creare tali modelli, dice il Trib. del distretto nord della Calofiornia Case No. 23-cv-03417-VC, 20 novembre 2023 , Kadrey v. Meta.

Nè nella costituzione dei modelli medesimi nè nell’output genrato dal loro uso:

<<1. The plaintiffs allege that the “LLaMA language models are themselves infringing
derivative works” because the “models cannot function without the expressive information
extracted” from the plaintiffs’ books. This is nonsensical. A derivative work is “a work based
upon one or more preexisting works” in any “form in which a work may be recast, transformed,
or adapted.” 17 U.S.C. § 101. There is no way to understand the LLaMA models themselves as a
recasting or adaptation of any of the plaintiffs’ books.

[più che altro non c’è prova: non si può dire che sia impossibile in astratto]
2. Another theory is that “every output of the LLaMA language models is an infringing
derivative work,” and that because third-party users initiate queries of LLaMA, “every output
from the LLaMA language models constitutes an act of vicarious copyright infringement.” But
the complaint offers no allegation of the contents of any output, let alone of one that could be  understood as recasting, transforming, or adapting the plaintiffs’ books. Without any plausible
allegation of an infringing output, there can be no vicarious infringement. See Perfect 10, Inc. v.
Amazon.com, Inc., 508 F.3d 1146, 1169 (9th Cir. 2007).
The plaintiffs are wrong to say that, because their books were duplicated in full as part of
the LLaMA training process, they do not need to allege any similarity between LLaMA outputs
and their books to maintain a claim based on derivative infringement. To prevail on a theory that
LLaMA’s outputs constitute derivative infringement, the plaintiffs would indeed need to allege
and ultimately prove that the outputs “incorporate in some form a portion of” the plaintiffs’
books. Litchfield v. Spielberg, 736 F.2d 1352, 1357 (9th Cir. 1984); see also Andersen v.
Stability AI Ltd., No. 23-CV-00201-WHO, 2023 WL 7132064, at *7-8 (N.D. Cal. Oct. 30, 2023)
(“[T]he alleged infringer’s derivative work must still bear some similarity to the original work or
contain the protected elements of the original work.”); 2 Melville B. Nimmer & David Nimmer,
Nimmer on Copyright § 8.09 (Matthew Bender Rev. Ed. 2023) (“Unless enough of the pre-
existing work is contained in the later work to constitute the latter an infringement of the former,
the latter, by definition, is not a derivative work.”); 1 Melville B. Nimmer & David Nimmer,
Nimmer on Copyright § 3.01 (Matthew Bender Rev. Ed. 2023) (“A work is not derivative unless
it has substantially copied from a prior work.” (emphasis omitted)). The plaintiffs cite Range
Road Music, Inc. v. East Coast Foods, Inc., 668 F.3d 1148 (9th Cir. 2012), but that case is not
applicable here. In Range Road, the infringement was the public performance of copyrighted
songs at a bar. Id. at 1151-52. The plaintiffs presented evidence (namely, the testimony of
someone they sent to the bar) that the songs performed were, in fact, the protected songs. Id. at
1151-53. The defendants presented no evidence of their own that the protected songs were not
performed. Nor did they present evidence that the performed songs were different in any
meaningful way from the protected songs. Id. at 1154. The Ninth Circuit held that, under these
circumstances, summary judgment for the plaintiffs was appropriate. And the Court rejected the
defendants’ contention that the plaintiffs, under these circumstances, were also required to
present evidence that the performed songs were “substantially similar” to the protected songs.
That contention made no sense, because the plaintiffs had already offered unrebutted evidence
that the songs performed at the bar were the protected songs. Id. at 1154. Of course, if the
defendants had presented evidence at summary judgment that the songs performed at the bar
were meaningfully different from the protected songs, then there would have been a dispute over
whether the performances were infringing, and the case would have needed to go to trial. At that
trial, the plaintiffs would have needed to prove that the performed songs (or portions of the
performed songs) were “substantially similar” to the protected songs. That’s the same thing the
plaintiffs would need to do here with respect to the content of LLaMA’s outputs. To the extent
that they are not contending LLaMa spits out actual copies of their protected works, they would
need to prove that the outputs (or portions of the outputs) are similar enough to the plaintiffs’
books to be infringing derivative works. And because the plaintiffs would ultimately need to
prove this, they must adequately allege it at the pleading stage>>

[anche qui manca la prova]

Motivazione un pò striminzita, per vero.

(notizia e link dal blog di Eric Goldman)

Ancora su AI, data scraping e violazione di copyright (questa volta per lo più negata)

La corte del distr. Nord della California  30 ottobre 2023, Case 3:23-cv-00201-WHO, Andersen v. Stability AI, DeviantArt, Midjourney, esamina il tema in oggetto (segnalazione e link di Jess Miers su X).

Le domande sono tutte rigettate tranne quelal verso Stability, per la quale è cocnessa facoltà di modifica:

<<3. Direct Infringement Allegations Against Stability Plaintiffs’ primary theory of direct copyright infringement is based on Stability’s creation and use of “Training Images” scraped from the internet into the LAION datasets and then used to train Stable Diffusion. Plaintiffs have adequately alleged direct infringement based on the allegations that Stability “downloaded or otherwise acquired copies of billions of copyrighted images without permission to create Stable Diffusion,” and used those images (called “Training Images”) to train Stable Diffusion and caused those “images to be stored at and incorporated into Stable Diffusion as compressed copies.” Compl. ¶¶ 3-4, 25-26, 57. In its “Preliminary Statement” in support of its motion to dismiss, Stability opposes the truth of plaintiffs’ assertions. See Stability Motion to Dismiss (Dkt. No. 58) at 1. However, even Stability recognizes that determination of the truth of these allegations – whether copying in violation of the Copyright Act occurred in the context of training Stable Diffusion or occurs when Stable Diffusion is run – cannot be resolved at this juncture. Id. Stability does not otherwise oppose the sufficiency of the allegations supporting Anderson’s direct copyright infringement claims with respect to the Training Images>>.

Provvedimento itneressante poer chi si occupa del tema, dato che da noi ancora non se ne son visti.