The recent proliferation of generative artificial intelligence (AI) technologies such as pre-trained large language models (LLMs) has opened up new frontiers in computational law. An exciting area of development is the use of AI to automate the deductive rule-based reasoning inherent in statutory and contract law. This paper argues that such automated deductive legal reasoning can now be viewed from the lens of software engineering, treating LLMs as interpreters of natural-language programs with natural-language inputs. We show how it is possible to apply principled software engineering techniques to enhance AI-driven legal reasoning of complex statutes and to unlock new applications in automated meta-reasoning such as mutation-guided example generation and metamorphic property-based testing.

翻译：近年来，预训练大语言模型等生成式人工智能技术的激增为计算法学开辟了新前沿。一个令人兴奋的发展方向是利用人工智能实现成文法与合同法中固有的、基于规则的演绎推理自动化。本文认为，此类自动化演绎法律推理现在可以从软件工程的视角加以审视，即将大语言模型视为具有自然语言输入的自然语言程序的解释器。我们展示了如何运用规范的软件工程技术来增强人工智能对复杂法规的推理能力，并解锁自动元推理中的新应用，例如突变引导的示例生成和基于变形的属性测试。