The Impact of Generative AI on UK Copyright Law

Thaler has also applied for patents in several countries for inventions created by his DABUS (Device for the Autonomous Bootstrapping of Unified Sentience) AI, with limited success. Gowling WLG is an international law firm comprising the members of Gowling WLG International Limited, an English Company Limited by Guarantee, and their respective affiliates. genrative ai Gowling WLG International Limited promotes, facilitates and co-ordinates the activities of its members but does not itself provide services to clients. AI promises remarkable productivity gains and, as a result, some politicians are straining to accommodate the needs of a new generation of tech giants in the hope that they will bring prosperity with them.

This blog post is just scratching the surface of the conflicts that are to come with regards to AI and copyright. I am sure that at some point an artist will try to sue one of the companies working in this area for copyright infringement. Assuming that the input phase is fine and the datasets used are legitimate, then most infringement lawsuits may end up taking place in the output phase. And it is here that I do not think that there will be substantive reproduction to warrant copyright infringement. On the contrary, the technology itself is encoded to try to avoid such a direct infringement from happening.

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But while copyright nerds obsess over the authorship question, the issue that is getting more attention from artists is that of copyright infringement. Adobe is also proposing that digital images contain explicit “do not train” tags, but artist-rights campaigners claim that existing copyright law means that artists should not have to explicitly opt-out of their work being used to train AI. Instead, they argue that AI tool creators must instead seek explicit prior approval for copyrighted work to be included in training databases. Generative artificial intelligence in deepfake content can be used to create fake videos and images, which can be used to spread misinformation, harass or blackmail individuals leading to major legal issues. This technology can also create realistic images of people, which can be used for malicious purposes such as catfishing and identity theft.

Deep learning utilises algorithms that repeatedly perform certain tasks, each time improving the result; for example, responding to questions about science or generating images. In order to improve the output results, the algorithm must be fed significant amounts of information to learn and improve the output. In this example, the algorithm would be given access to considerable amounts of scientific information, data and research, or should be given access to art works and photography. Nova Productions Ltd v Mazooma Games Ltd [2007] EWCA Civ 219 did look at this issue to some extent, although the facts are not entirely identical to an AI generated scenario. Nevertheless, the finding that the creators of the game were the authors, and copyright owners, of various screenshots made by a player playing the game, is useful in understanding the direction in which s.9(3) may be interpreted. It may therefore suggest that the copyright owner of AI generated images and literary content is the creator of the AI technology, rather than the user.

Intellectual property rights of AI-generated works: Who owns the rights created by artificial intelligence systems?

“Based on the Office’s understanding of the generative AI technologies currently available, users do not exercise ultimate creative control over how such systems interpret prompts and generate material,” the office said. The question of who owns the rights to works of art created by AI will go before the courts, as individual artists as well as corporations, challenge the right of AI service providers to use their works without permission. We will undoubtedly discuss much more in the future regarding the legal issues of generative artificial intelligence.

Thaler had tried multiple times to copyright the image “as a work-for-hire to the owner of the Creativity Machine,” listing the author as the creator of the work and Thaler as the artwork’s owner. The main idea behind creative AI is to train a system in a way that it can generate outputs that statistically resemble their training data, in other words, in order to generate poetry, you train the AI with poetry, if you want it to generate faces, you train it with faces. There are various models for generative AI, but the two main ones are generative adversarial networks (GANs) and diffusion models. In the EU, the Digital Single Market Directive has also opened the door for wider adoption of text and data mining. AI is relatively unproblematic when doing things like running security audits, analysing data, and answering customer service questions as part of the latest call centre technology trends.

The use of AI tools should be continually monitored, and the AI strategy generally kept under review. The capabilities of generative AI are changing rapidly and so too will the contractual terms of use and (eventually) the law in this area, and businesses need to be prepared. The copyright eligibility of such works, according to the Office, will hinge on the specifics of how the AI tool was employed and operated to generate genrative ai the final product. It should be noted that the CDPA 1988 permits various acts to be carried out in relation to copyright works notwithstanding the subsistence of copyright. There are a significant number of permitted acts, many of which only apply in very specific circumstances and are beyond the scope of this article. The government expects parties to enter into the final code of practice on a voluntary basis.

This may depend on the amount of information put in by the user, which could change the assessment of whose creativity is expressed in the output. The issue of whether AI-generated art can be protected under copyright laws has been a contentious topic, with various opinions and viewpoints. The U.S. Copyright Office has taken the position that creations made by non-human entities, including machines, are not eligible for copyright protection.

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But, I’m fully on board with exploring the potential of the technology while we figure it out. Augusto Preta is a consultant, economist and market analyst, with long-established experience in the field of content media and digital markets. As Founder and CEO at ITMedia Consulting, he has assisted and advised for almost 30 years, public institutions, authorities and major companies in media, telecommunications and the internet industries. This page is dedicated to keeping readers informed of the latest news and thought leadership articles from
law firms across the globe. This article will explore the major shortcomings of the Arrangement Model in attributing copyright to AI-generated works. It also seems to match the “sweat of the brow” intellectual property doctrine, which states whoever has the skill and puts in the time and effort to create the work deserves protection.

• The Panelists will address generative AI’s status, its future, its legal implications, some of which is in current litigation, and how it will impact our IP transactions, with special attention to stage of AI concerned with ingesting data (training).
• The US Copyright Office released a statement in March 2023, in an attempt to clarify its position on AI-generated works.
• The scale of the datasets in question also makes them challenging to audit effectively to ensure that any list of copyrighted material published by a developer is truly exhaustive.
• The output can be improved by feeding prompts to the machine that “learns” by further refining its data analysis to find more complex and efficient patterns without the developers’ intervention or input.

So far in the US civil litigation has naturally begun on the issue of sourcing and scraping and the storage of data. The argument is that this tech violates copyright licence, particularly attribution storage and use, that it violates DMCA requirements, privacy law, passing off genrative ai requirements, and that all of these violations are unjustly enriching the tech companies that have benefitted from them. One of the most important elements of FIPP Congress is the way that media companies share best practice in how they have begun to experiment with technology.

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However, in June 2022, the UK IPO announced a proposal to allow TDM for any purpose whatsoever. The proposed exception would have allowed commercial AI tools to be trained on all copyright-protected works without requiring a licence or compensating rightsholders, making the UK one of the most permissive places for AI research in the world. The UK Government then announced in February 2023 that these proposals were to be scrapped.

Equally, it’s imperative that regulatory measures evolve in tandem with these technological advancements. This balance is crucial to safeguard intellectual property rights while fostering an environment conducive to technological innovation and growth. The future will demand a harmonised, international approach to successfully navigate this intricate confluence of AI and copyright law. All it can do is run pre-existing material through its algorithm and recreate it in ways that answer the command it’s been given.