#EU#Spain#Copyright#IP#FairUse#NFTs: "The importance of the 11 January 2024 judgment of Barcelona Commercial Court number 9 lies in the fact that it is the first Spanish decision that pronounces on whether the owner of certain works of art is legally allowed to create NFTs from them, without the consent of the copyright holders. However, it does not seem that the doctrine of this judgment can be generalized to other cases; instead, it calls for an assessment to be made on a case-by-case basis. Furthermore, it is debatable whether the creation of NFTs can be considered “fair use”, since (i) this generates a “new” public and a new “digital” market for artworks that, to date, only existed in the real world and (ii) it deprives de facto copyright holders of a potential source of income. VEGAP has announced that it has appealed this judgment. Thus, the duel between NFTs and copyright holders was just the first skirmish in a battle that has ended, for the time being, in the NFTs’ favour. We will have to keep an eye out for the second round. Who will be the next victor, the NFTs or the authors? Place your bets!"
#AI#GenerativeAI#AITraining#Copyright#FairUse#IP#DataCommons#Books: "This paper is a snapshot of an idea that is as underexplored as it is rooted in decades of existing work. The concept of mass digitization of books, including to support text and data mining, of which AI is a subset, is not new. But AI training is newly of the zeitgeist, and its transformative use makes questions about how we digitize, preserve, and make accessible knowledge and cultural heritage salient in a distinct way.
As such, efforts to build a books data commons need not start from scratch; there is much to glean from studying and engaging existing and previous efforts. Those learnings might inform substantive decisions about how to build a books data commons for AI training. For instance, looking at the design decisions of HathiTrust may inform how the technical infrastructure and data management practices for AI training might be designed, as well as how to address challenges to building a comprehensive, diverse, and useful corpus. In addition, learnings might inform the process by which we get to a books data commons — for example, illustrating ways to attend to the interests of those likely to be impacted by the dataset’s development." https://openfuture.pubpub.org/pub/towards-a-book-data-commons-for-ai-training/release/1
#AI#GenerativeAI#EU#AIAct#Copyright#AITraining#IP#FairUse: "Scarcely a day goes by without news of exciting breakthroughs in the world of AI. In the face of disruptive waves of technological change and mounting uncertainty, the law cannot help but take on an “experimental” character, with lawmakers and lawyers often caught on the back foot, struggling to keep up with the sweeping winds of change. But whatever the next steps may be, one thing is certain: litigation surrounding generative AI marks an important crossroads, and whichever path we choose is likely to shape the future of the technology. The rising litigation around generative AI is not targeting image by image or specific excerpts of infringing texts produced by AI models. Rather, the whole technique behind the system is hanging in the balance.
Another key takeaway that merits attention relates to the fragmentary landscape of copyright that seems to be unfolding in the wake of the rapid advances in AI technology. Although the emerging European legal framework offers strict rules yet solid ground for AI technology to flourish on the continent, it’s worth wondering what will happen if the “Brussels effect” fails to reach the shores the other side of the Atlantic and the use of copyrighted works for training purposes is found to be transformative fair use in common law jurisdictions, while a relevant portion of these works are opted-out of AI models on European soil. That would mark a yawning gap between two copyright regimes, opening a new chapter in this old tale and potentially disadvantaging would-be European generative AI providers." https://copyrightblog.kluweriplaw.com/2024/04/08/the-stubborn-memory-of-generative-ai-overfitting-fair-use-and-the-ai-act/
Many maintain that their broad use of copyrighted material is legal under the doctrine of "fair use," which courts apply using a complex four-part standard.
However, as Giordano notes, "the public status of copyrighted material" is not one of those factors.
A decade ago, the Google Books decision held that Google's use of "text snippets" to catalogue published works was an acceptable fair use, and AI companies often point to Google's win to back their argument.
The second argument is that copyright is not an issue in AI training because AI systems don't copy material: They just "learn" from it the way a human might.
Reality check: AI companies often refuse to say which "publicly available" data they are using, with OpenAI and others describing their sources as a competitive trade secret."
Today's use for an AI chatbot, fixing OCR errors and artifacts from text exported from scanned PDF, then reformatting text with proper paragraph breaks to copy/paste into more readable format #FairUse
All streams for REMIX CULTURE WEEK 2024 are now live and available to view until Sunday, March 3 @ 9PM EST. Make sure to catch em' before they're gone: https://www.twitch.tv/substreamtv ☢️
RCW 2024 concludes tonight @ 8PM at Eberle Studios in Homestead, PA with Craig Baldwin's fair use collage doc SONIC OUTLAWS on 16mm film. See you there!
This headline amuses me because it completely admits where we are. At one point cutting the cord meant you saved money.
But now? It's gone full circle back to where we were. Everything is the same price and we're just admitting that its all #Cable#Enshittification#Capitalism
RT @katecrawford
✨Just published: New @ISSUESinST collection of STS scholars addressing the urgent governance challenges of generative AI. This came from our year-long @ENS_ULM working group, where we each focused on one core problem:
#AI#GenerativeAI#AITraining#Copyright#FairUse#IP: "Copyright law was developed by eighteenth-century capitalists to intertwine art with commerce. In the twenty-first century, it is being used by technology companies to allow them to exploit all the works of human creativity that are digitized and online. But the destabilization around generative AI is also an opportunity for a more radical reassessment of the social, legal, and cultural frameworks underpinning creative production.
(...)
It may be time to develop concepts of intellectual property with a stronger focus on equity and creativity as opposed to economic incentives for media corporations. We are seeing early prototypes emerge from the recent collective bargaining agreements for writers, actors, and directors, many of whom lack copyrights but are nonetheless at the creative core of filmmaking. The lessons we learn from them could set a powerful precedent for how to pluralize intellectual property. Making a better world will require a deeper philosophical engagement with what it is to create, who has a say in how creations can be used, and who should profit." https://issues.org/generative-ai-copyright-law-crawford-schultz/
#AI#GenerativeAI#GeneratedImages#Copyright#AITraining#FairUse: "The datasets on which GAI systems like ChatGPT and Stable Diffusion rely are more like Google Books than commercial web crawlers that gather data; GAI systems need writing and art in its complete form to train from. And the comparison to Google Books doesn’t stop there. Many GAI systems are built using third-party public datasets like Common Crawl and LAION that are distributed under fair use principles and provide a real public good: archiving and making accessible the aggregated content of the internet for academics, researchers, and anyone else that may want it. These are free, non-commercial datasets collected by nonprofit organizations for use by researchers and the public. Web crawling and scraping also underlie the operation of search engines and archiving projects like the Internet Archive’s popular Wayback Machine.
In other words, the same practices that go into collecting data for GAI training are currently understood to be non-infringing or protected by fair use. Considering how vital these practices are for an open and accessible internet, we should ensure that they stay that way.
As a threshold matter, it is critical to understand that accessing, linking to, or interacting with digital information does not infringe any copyright. Reading a book, looking at a photograph, admiring a painting, or listening to music is not, and never should be, copyright infringement. This is not a “fair use” issue; the ability to use, access, or interact with a creative work is outside a copyright owner’s scope of control. Based on the best explanations of how GAI systems work, training a GAI system is generally analogous to these kinds of uses."
IEEE Spectrum: Generative AI Has a Visual Plagiarism Problem
Experiments with Midjourney and DALL-E 3 show a copyright minefield (Image: AI generated)
" Recent empirical work has shown that LLMs are in some instances capable of reproducing, or reproducing with minor changes, substantial chunks of text that appear in their training sets. "
@ai6yr That's the kind of stuff that makes me concerned about copyright, though Jeff Jarvis @jeffjarvis pointed out in his comments to the Senate that copyright was meant to protect INDIVIDUAL creators, not corporate creators. From that perspective, the output you shared would be an example of Fair Use. #FairUse#copyright#creditright
@ai6yr Now that I've written that (and after thanking you for giving me the chance to think about this through writing), it occurs to me that the principle of 'copyright for creators' gets complicated in academic publishing.
Say I publish a paper in a journal. As part of the contract I sign with the journal, I give my copyright to them for the paper. Now, my creative work is somewhere between 'individual content' and 'corporate asset'. Jeff Jarvis @jeffjarvis would say that using my paper to train a LLM would be Fair Use. I'm not sure how I feel about that.
On the other hand, this example of his provocative idea about 'creditright' starts making more sense. The journal can hold my copyright, but I continue to retain my 'creditright' in perpetuity.
(Note to self: find more information on this 'creditright' idea.)
📰 The New York Times sues ChatGPT creator OpenAI, Microsoft, for copyright infringement
ᐅ @NPR
「 In addition, the Times' legal team is asking a court to order the destruction of all large language model datasets, including ChatGPT, that rely on the publication's copyrighted works 」
well fuck #PaulaDeen ('s legal team) that's stupid as hell.
A hyper-edited video of her saying "now put it in the oven for 350 hours at 3 degrees" does not harm your #copyright (fuck all copyright btw) and is obviously #Fairuse due to being transformative and useless as a replacement of the original work
But the principle that "Pseudo-#IP Rules Shouldn't Block Free Speech" has the nice side effect of highlighting what's wrong with this otherwise unrelated effort:
I did this #SailorMoon outfit better in the winter when we used it (with other accessories) to play a game of "Copyright or wrong?" but it still makes me happy on the day we're talking #copyright and #fairuse in #AI class. #DHsewing
It would need some analysis by legal experts. But consider that archive.org gets away with it. Although archive.org has an opt-out mechanism. So perhaps each Lemmy instance should have an opt-out mechanism, which should push a CAPTCHA in perhaps one of few good uses for CAPTCHAs. Then if Quora wants to opt-out, they have to visit every Lemmy instance, complete the opt-out form, and solve the CAPTCHA. Muahaha!
Note as well how 12ft.io works: it serves you Google’s cache of a site (which is actually what the search index uses). How did Google get a right to keep those caches?
There’s also the #fairUse doctrine. You can quote a work if your commenting on it. Which is what we do in the threadiverse. Though not always – so perhaps the caching should be restricted to threads that have comments.
This week on my podcast, I read my recent @medium column, "How To Think About #Scraping: In #privacy and #labor fights, copyright is a clumsy tool at best," which proposes ways to retain the benefits of scraping without the privacy and labor harms that sometimes accompany it:
If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
This is canonical #FairUse, the kind of copying that almost always involves overriding the objections of the site's proprietor. Not all adversarial scraping is good, but this sure is.
There's an argument that scraping the news-sites without permission might piss them off, but it doesn't bring them any real harm. But even when scraping harms the scrapee, it is sometimes legitimate - and necessary.
"There will be no new books, songs or plays added to the public domain in Canada until 2043…The change brings Canada into compliance with a commitment it made under the new North American free trade deal to match its copyright protections with those in place in the United States since 1998."
The same US copyright orgs "argue that academic freedom would be threatened if scientists have the right to freely share the results of Government-funded research."
Bug: people are posting paywalls & other exclusive walled gardens
The problem:...