人工智能伦理的趋同性？使用多框架方法分析大型语言模型中的道德基础优先级
The Convergent Ethics of AI? Analyzing Moral Foundation Priorities in Large Language Models with a Multi-Framework Approach
AI总结：
本文提出PRIME框架，通过双协议方法评估六个领先LLM的道德优先级，发现它们在道德决策中表现出显著的趋同性，与人类道德偏好高度一致，为AI伦理基准测试提供了可扩展方法。
摘要：
随着大型语言模型（LLM）日益被部署于具有重大影响的决策场景中，系统性地评估其伦理推理能力成为一项关键要务。本文提出了推理与内在道德评估优先级（PRIME）框架——一种用于分析跨基础伦理维度道德优先级的综合方法，这些维度包括后果主义-义务论推理、道德基础理论和Kohlberg发展阶段。我们通过结合直接提问和对既定伦理困境的响应分析的双协议方法，将该框架应用于六个领先的LLM。我们的分析揭示了显著的趋同模式：所有评估模型均表现出对关爱/伤害和公平/欺骗基础的强烈优先级，同时持续低估权威、忠诚和纯洁维度。通过对置信度指标、响应 reluctance 模式和推理一致性的详细检查，我们确立当代LLM（1）产生果断的伦理判断，（2）在道德决策中展示显著的跨模型一致性，以及（3）通常与经验确立的人类道德偏好相对应。本研究为伦理基准测试贡献了一种可扩展、可延伸的方法，同时突出了当前AI道德推理架构中既有的前景能力和系统性局限——这些洞察对于这些系统承担日益重要的社会角色时的负责任发展至关重要。
英文摘要：
As large language models (LLMs) are increasingly deployed in consequential decision-making contexts, systematically assessing their ethical reasoning capabilities becomes a critical imperative. This paper introduces the Priorities in Reasoning and Intrinsic Moral Evaluation (PRIME) framework--a comprehensive methodology for analyzing moral priorities across foundational ethical dimensions including consequentialist-deontological reasoning, moral foundations theory, and Kohlberg's developmental stages. We apply this framework to six leading LLMs through a dual-protocol approach combining direct questioning and response analysis to established ethical dilemmas. Our analysis reveals striking patterns of convergence: all evaluated models demonstrate strong prioritization of care/harm and fairness/cheating foundations while consistently underweighting authority, loyalty, and sanctity dimensions. Through detailed examination of confidence metrics, response reluctance patterns, and reasoning consistency, we establish that contemporary LLMs (1) produce decisive ethical judgments, (2) demonstrate notable cross-model alignment in moral decision-making, and (3) generally correspond with empirically established human moral preferences. This research contributes a scalable, extensible methodology for ethical benchmarking while highlighting both the promising capabilities and systematic limitations in current AI moral reasoning architectures--insights critical for responsible development as these systems assume increasingly significant societal roles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
