用形式化逻辑验证AI是否合乎伦理,发现真实系统存在公平性缺陷。
Deontic Temporal Logic for Formal Verification of AI Ethics
- 基于义务逻辑与时间算子构建AI伦理形式化框架
- 自动证明显示两个真实系统不满足关键公平性要求
- 适合关注AI伦理验证的开发者与政策制定者
随着人工智能系统日益普及和影响扩大,确保其合乎伦理行为成为全球关注焦点。本文提出一种基于义务逻辑的形式化方法,用于定义和验证AI系统的伦理行为,聚焦系统级规范。通过引入公理与定理,捕捉与公平性和可解释性相关的伦理要求,并结合时间算子对系统随时间演变的伦理行为进行推理。作者以真实世界的COMPAS和贷款预测AI系统为案例,将多种伦理属性编码为义务逻辑公式,利用自动化定理证明器验证这些系统是否满足设定属性。形式化验证结果显示,两个系统均未能满足与公平性和非歧视相关的若干核心伦理属性,证明了该方法在识别实际应用中潜在伦理问题上的有效性。
原文摘要 · Abstract (English)
Ensuring ethical behavior in Artificial Intelligence (AI) systems amidst their increasing ubiquity and influence is a major concern the world over. The use of formal methods in AI ethics is a possible crucial approach for specifying and verifying the ethical behavior of AI systems. This paper proposes a formalization based on deontic logic to define and evaluate the ethical behavior of AI systems, focusing on system-level specifications, contributing to this important goal. It introduces axioms and theorems to capture ethical requirements related to fairness and explainability. The formalization incorporates temporal operators to reason about the ethical behavior of AI systems over time. The authors evaluate the effectiveness of this formalization by assessing the ethics of the real-world COMPAS and loan prediction AI systems. Various ethical properties of the COMPAS and loan prediction systems are encoded using deontic logical formulas, allowing the use of an automated theorem prover to verify whether these systems satisfy the defined properties. The formal verification reveals that both systems fail to fulfill certain key ethical properties related to fairness and non-discrimination, demonstrating the effectiveness of the proposed formalization in identifying potential ethical issues in real-world AI applications.
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