Generative AI
Generative AI (GenAI)– refers to artificial intelligence technologies that use algorithms capable of producing new content, such as text, images, music, and code, from the training data they are provided with. These technologies primarily utilize advanced machine learning frameworks, including deep learning models, to analyze and replicate complex patterns found in existing data, allowing them to generate novel content that is not a direct copy of their training inputs.[1] EU AI Act stipulates that generative AI models are a typical example for a general-purpose AI model, given that they allow for flexible generation of content, such as in the form of text, audio, images or video, that can readily accommodate a wide range of distinctive tasks.[2]
Key applications of GenAI include:
- Creative Arts: generating original artworks, music compositions, and literary pieces;[3]
- Software Development: automating coding tasks and assist in software creation;[4]
- Business and Marketing: generating personalized content for advertising and customer engagement;[5]
- Scientific Research: simulating data sets and modeling experimental outcomes[6]
AI, including its generative form, comes in different forms and should not be treated as a single synthetic entity. The quality of content generated by GenAI relies mostly on the data used to train it.[7]
Legal implications
As GenAI evolves, it brings with it significant legal considerations. These include concerns over the originality and ownership of AI-generated content, the potential for producing deceptive or biased content, and broader impacts on copyright laws.
As generative AI continues to develop, it introduces complex legal challenges, particularly in the realms of copyright, patent law, and liability. Understanding the legal aspects of generative AI involves exploring how these technologies intersect with existing laws and what new regulations might be needed to address the unique challenges they pose.[8]
One of the primary legal issues with generative AI revolves around copyright. Since AI systems can produce artworks, music, and literary work that might closely resemble or even surpass human-created works, questions arise regarding who holds the copyright — the programmer, the user, the AI itself, or no one at all.[9]
Based on European principles, any use of copyright protected content requires the authorization of the rightsholder concerned unless relevant copyright exceptions and limitations apply. Directive (EU) 2019/790 introduced exceptions and limitations allowing reproductions and extractions of works or other subject matter, for the purpose of text and data mining, under certain conditions. Under these rules, rightsholders may choose to reserve their rights over their works or other subject matter to prevent text and data mining, unless this is done for the purposes of scientific research. Where the rights to opt out has been expressly reserved in an appropriate manner, providers of general-purpose AI models need to obtain an authorization from rightsholders if they want to carry out text and data mining over such works.[10]
GenAI also impacts patent law, particularly concerning the patentability of AI-generated inventions. The U.S. Patent and Trademark Office has been grappling with whether inventions created by AI can be patented and, if so, who qualifies as the inventor.[11]
Another critical legal aspect is liability in cases where AI-generated solutions lead to harm or financial loss. Determining who is responsible—the AI developer, the user, or the AI itself—is complicated and still being debated.[12]
The legal implications of using generative AI in esports are multifaceted and can touch upon various aspects of intellectual property law, contract law, and potentially even criminal law, depending on the specific circumstances. Both organizations and esports players should use AI responsibly to avoid potential liability for violating the rights described above.
[1] Stanford University’s “Artificial Intelligence and Life in 2030 https://ai100.stanford.edu/sites/g/files/sbiybj18871/files/media/file/ai100report10032016fnl_singles.pdf accessed 28.04.2024, passim.
[2] Recital (99) of EU Artificial Intelligence Act (“AI Act”).
[3] <https://blog.adobe.com/en/publish/2023/10/18/generation-ai-reimagining-creativity-with-generative-ai> accessed 28.04.2024.
[4] D. Coldewey, ‘Age of AI: Everything you need to know about artificial intelligence’ (Techcrunch, 2023) <https://techcrunch.com/2023/08/04/age-of-ai-everything-you-need-to-know-about-artificial-intelligence/> accessed 28.04.2024.
[5] T. H. Davenport and N.Mittal, ‘How Generative AI Is Changing Creative Work’ Harvard Business Review <https://hbr.org/2022/11/how-generative-ai-is-changing-creative-work> accessed 28.04.2024
[6] <https://www.nature.com/nature-portfolio/editorial-policies/ai>
[7] See definition for “Artificial Intelligence (AI)” Esports Legal News Wiki.
[8] A. Häuselmann, ‘Disciplines of AI: An Overview of Approaches and Techniques’ In B. Custers & E. Fosch-Villaronga (Eds.), Law and Artificial Intelligence Regulating AI and Applying AI in Legal Practice (T.M.C. ASSER PRESS 2022), pp. 47-67.
[9] C. Walsh, ‘How to think about AI’ <https://hls.harvard.edu/today/how-to-think-about-ai/> accessed 28.04.2024.
[10] Recital (105) of EU Artificial Intelligence Act (“AI Act”).
[11] B. Brittain, ‘Patents on AI creations require ‘significant’ human input, USPTO says’ <https://www.reuters.com/legal/litigation/patents-ai-creations-require-significant-human-input-uspto-says-2024-02-12/> accessed 28.04.2024.
[12] E. Kahana, ‘AI Liability: When “Intelligent Deviation” is Undesirable’ <https://law.stanford.edu/2020/02/26/ai-liability-when-intelligent-deviation-is-undesirable/> accessed 28.04.2024.
