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October 28, 2024Ā· 2024 IEEE 6th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)
conference-paper

Bridging the Legal Divide: Contractual Enforceability and Acceptability in the AI-Driven Automated Conversion of Smart Legal Contracts

Authors:S. BalajiRam DantuKritagya UpadhyayThomas McCullough

Abstract

Many people find the legal system to be convoluted and resource-intensive with all of the complications, which often derive from the vagueness and ambiguity of legal texts, that arise in its processes. Oftentimes, legal processes become inconvenient or even inaccessible to parts of the general population. The integration of artificial intelligence (AI) and blockchain technology into legal processes, particularly in the interpretation of contract transactions, promises to revolutionize the legal field by enhancing efficiency and reducing human intervention. The conversion of legal contracts into smart contracts specifically has the power to make legal transactions auto-executable and instantaneous. However, this convergence introduces a significant challenge in how to automate the process of converting a legal contract, written in text, into a smart contract, written in code. This paper presents a comprehensive evaluation of how artificial intelligence can achieve complete automation of this conversion by generating legal contract interpretations and employing a dual-framework analysis based on the metrics of Enforceability and Acceptability. Through an in-depth examination of the opinions of legal professionals and AI-generated contract interpretations, we explore the extent to which AI can reliably interpret the vagueness and ambiguity in legal texts through interpretations and translate legal language into smart contract code while adhering to legal standards and ethical considerations. This paper contributes to the ongoing discourse on the role of AI and smart contracts in law, proposing a strategy to make the legal system more accessible and offering insights for legal practitioners, AI developers, and policymakers on navigating the complexities of AI-driven legal interpretations.

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