Alignment of artificial intelligence (AI) encompasses the normative problem of specifying how AI systems should act and the technical problem of ensuring AI systems comply with those specifications. To date, AI alignment has generally overlooked an important source of knowledge and practice for grappling with these problems: law. In this paper, we aim to fill this gap by exploring how legal rules, principles, and methods can be leveraged to address problems of alignment and inform the design of AI systems that operate safely and ethically. This emerging field -- legal alignment -- focuses on three research directions: (1) designing AI systems to comply with the content of legal rules developed through legitimate institutions and processes, (2) adapting methods from legal interpretation to guide how AI systems reason and make decisions, and (3) harnessing legal concepts as a structural blueprint for confronting challenges of reliability, trust, and cooperation in AI systems. These research directions present new conceptual, empirical, and institutional questions, which include examining the specific set of laws that particular AI systems should follow, creating evaluations to assess their legal compliance in real-world settings, and developing governance frameworks to support the implementation of legal alignment in practice. Tackling these questions requires expertise across law, computer science, and other disciplines, offering these communities the opportunity to collaborate in designing AI for the better.

翻译：人工智能对齐包含两个层面：规范性问题，即界定人工智能系统应如何行动；技术性问题，即确保人工智能系统遵循这些规范。迄今为止，人工智能对齐研究普遍忽视了一个应对这些问题的重要知识来源与实践领域：法律。本文旨在填补这一空白，探讨如何利用法律规则、原则及方法来应对对齐问题，并为设计安全且符合伦理的人工智能系统提供参考。这一新兴领域——法律对齐——聚焦于三个研究方向：（1）设计人工智能系统以遵循通过合法制度与程序制定的法律规则内容；（2）借鉴法律解释方法以指导人工智能系统的推理与决策过程；（3）运用法律概念作为应对人工智能系统中可靠性、信任与合作挑战的结构性蓝图。这些研究方向提出了新的概念性、实证性与制度性问题，包括探究特定人工智能系统应遵循的具体法律集合，创建评估体系以衡量其在真实场景中的合规性，以及构建治理框架以支持法律对齐在实践中的实施。解决这些问题需要融合法学、计算机科学及其他领域的专业知识，为相关学界提供了协作设计更优人工智能的重要契机。