安全与伦理人工智能的法律对齐

摘要

人工智能对齐（AI Alignment）包含两大核心问题：一是规范性问题，即明确人工智能系统应如何行动；二是技术性问题，即确保人工智能系统符合这些规范。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与实践来源——法律。本文旨在通过探索如何运用法律规则、原则及方法来应对对齐问题，并为设计安全合规、符合伦理的人工智能系统提供参考，从而填补这一空白。这一新兴领域——法律对齐——聚焦三个研究方向：（1）设计能够遵循经由合法制度与程序制定的法律规则内容的人工智能系统；（2）借鉴法律解释方法指导人工智能系统的推理与决策过程；（3）运用法律概念作为解决人工智能系统可靠性、信任度与合作性挑战的结构性蓝图。这些研究方向催生了新的概念性、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体系，创建评估其在真实场景中合法合规性的方法，以及构建支持法律对齐实践落地的治理框架。解决这些问题需要融合法学、计算机科学等多学科专业知识，为不同学界提供了共同设计更美好人工智能的合作契机。

English

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.

安全与伦理人工智能的法律对齐

Legal Alignment for Safe and Ethical AI

摘要

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