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AI-Generated Texts and the Legal Landscape: A Technical Perspective



Artificial Intelligence (AI) has significantly disrupted the competitive marketplace, particularly in the realm of text generation. AI systems like ChatGPT and Bard have been used to generate a wide array of literary and artistic content, including translations, news articles, poetry, and scripts[8]. However, this has led to complex issues surrounding intellectual property rights and copyright laws[8].


Copyright Laws and AI-Generated Content


AI-generated content is produced by an inert entity using an algorithm, and therefore, it does not traditionally fall under copyright protection[8]. However, the U.S. Copyright Office has recently shown openness to granting ownership to AI-generated work on a "case-by-case" basis[5]. The key factor in determining copyright is the extent to which a human had creative control over the work's expression[5].


The AI software code itself is subject to copyright laws, and this includes the copyrights on the programming code, the machine learning model, and other related aspects[8]. However, the classification of AI-generated material, such as writings, text, programming code, pictures, or images, and their eligibility for copyright protection is contentious[8].


Legal Challenges and AI


The New York Times (NYT) has recently sued OpenAI and Microsoft for copyright infringement, contending that millions of its articles were used to train automated chatbots without authorization[2]. OpenAI, however, has argued that using copyrighted works to train its technologies is fair use under the law[6]. This case highlights the ongoing legal battle over the unauthorized use of published work to train AI systems[2].


Paraphrasing and AI


Paraphrasing tools, powered by AI, have become increasingly popular. These tools can rewrite, enhance, and repurpose content while maintaining the original meaning[7]. However, the use of such tools has raised concerns about the potential for copyright infringement and plagiarism.

To address this, it is suggested that heuristic and semantic protocols be developed for accepting and rejecting AI-generated texts[3].

Figure 1: AI Paraphrasing Tools

AI-based paraphrasing tools, such as Quillbot and SpinBot, offer the ability to rephrase text while preserving the original meaning. These tools can be beneficial for students and professionals alike, aiding in the writing process by providing alternative expressions and avoiding plagiarism. However, the accuracy and ethical use of these tools are concerns. For example, a student might use an AI paraphrasing tool to rewrite an academic paper, but without a deep understanding of the content, the result could be a superficial or misleading representation of the original work. This raises questions about the integrity of the paraphrased content and the student's learning process. It's crucial to develop guidelines for the ethical use of paraphrasing tools, ensuring that users engage with the original material and properly attribute sources to maintain academic and professional standards.


Citation and Referencing in the AI Era


The advent of AI-generated texts has necessitated a change in the concept of citation and referencing. Currently, the American Psychological Association (APA) recommends that text generated from AI be formatted as "Personal Communication," receiving an in-text citation but not an entry on the References list[4]. However, as AI-generated content becomes more prevalent, the nature of primary and secondary sources might change, and the traditional system of citation may need to be permanently altered.


For instance, the Chicago Manual of Style advises treating AI-generated text as personal communication, requiring citations to include the AI's name, the prompt description, and the date accessed. However, this approach may not be sufficient as AI becomes more prevalent in content creation.

Hypothetically, consider a scenario where a researcher uses an AI tool to draft a section of a literature review. The current citation standards would struggle to accurately reflect the AI's contribution, potentially leading to issues of intellectual honesty and academic integrity. As AI-generated content becomes more sophisticated, the distinction between human and AI authorship blurs, prompting a need for new citation frameworks that can accommodate these changes.


Content Protection and AI


The rise of AI has also raised concerns about the protection of gated knowledge and content. Publishing entities like NYT and Elsevier may need to adapt to the changing landscape[1].


The protection of original content in the age of AI is a growing concern, especially for publishers and content creators. The New York Times' lawsuit against OpenAI over the use of its articles to train AI models without permission exemplifies the legal challenges in this domain. To safeguard content, publishers might consider implementing open-source standards for data scraping and human-in-the-loop grammatical protocols.


Imagine a small online magazine that discovers its articles are being repurposed by an AI without credit or compensation. To combat this, the magazine could employ open-source tools to track the use of its content and ensure that any AI-generated derivatives are properly licensed and attributed, thus maintaining control over its intellectual property.

The rapid advancement of AI technologies has brought about significant changes in the legal and technical landscape. As AI continues to evolve, it is crucial to address the legal implications of AI-generated texts and develop protocols to regulate their use. This will ensure the protection of intellectual property rights while fostering innovation in AI technologies.


 

References


Unless otherwise specified, the opinions expressed in the articles published by Visual Legal Analytica, the digital publication are those of the authors. They do not reflect the opinions or views of Indic Pacific Legal Research LLP or its members.

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