用模糊逻辑表达社会伦理规则，让AI更懂复杂道德情境
Fuzzy Representation of Norms
- 用模糊逻辑构建SLEEC伦理规则的可计算表示
- 通过测试得分语义实现伦理规则的渐进式满足
- 适合研究AI伦理与人机信任的学者与工程师
由人工智能驱动的自主系统（AS）正日益融入日常生活与社会结构，引发对其伦理与社会影响的担忧。为建立可信性，AS必须遵循伦理原则与价值观。近年来，SLEEC（社会、法律、伦理、共情、文化）规则框架被提出，用于全面表征伦理与规范性考量。本文提出一种基于逻辑的SLEEC规则表示方法，并引入测试得分语义与模糊逻辑的嵌入机制，以处理伦理困境。该方法将伦理视为可能性领域，支持对模糊或冲突情境的渐进式响应。通过案例研究验证了其可行性。
原文摘要 · Abstract (English)
Autonomous systems (AS) powered by AI components are increasingly integrated into the fabric of our daily lives and society, raising concerns about their ethical and social impact. To be considered trustworthy, AS must adhere to ethical principles and values. This has led to significant research on the identification and incorporation of ethical requirements in AS system design. A recent development in this area is the introduction of SLEEC (Social, Legal, Ethical, Empathetic, and Cultural) rules, which provide a comprehensive framework for representing ethical and other normative considerations. This paper proposes a logical representation of SLEEC rules and presents a methodology to embed these ethical requirements using test-score semantics and fuzzy logic. The use of fuzzy logic is motivated by the view of ethics as a domain of possibilities, which allows the resolution of ethical dilemmas that AI systems may encounter. The proposed approach is illustrated through a case study.
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