Revolutionizing Legal Drafting: Leveraging Artificial Intelligence for Efficient Legal Work

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publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Revolutionizing Legal Drafting: Leveraging Artificial Intelligence for Efficient Legal Work</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shreya%20Poddar">Shreya Poddar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice. <iframe src="https://publications.waset.org/abstracts/179280.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI-driven%20legal%20drafting" title="AI-driven legal drafting">AI-driven legal drafting</a>, <a href="https://publications.waset.org/abstracts/search?q=legal%20automation" title=" legal automation"> legal automation</a>, <a href="https://publications.waset.org/abstracts/search?q=futureoflegalwork" title=" futureoflegalwork"> futureoflegalwork</a>, <a href="https://publications.waset.org/abstracts/search?q=largelanguagemodels" title=" largelanguagemodels"> largelanguagemodels</a> </p> <a 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Revolutionizing Legal Drafting: Leveraging Artificial Intelligence for Efficient Legal Work