分析八个大语言模型的伦理逻辑
Analyzing the Ethical Logic of Eight Large Language Models
AI总结：
研究分析OpenAI等八个大语言模型的伦理逻辑，通过让模型回答伦理原则问题和道德困境，用多种理论分析其回答，发现模型伦理判断趋同但在做决定意愿等方面有差异，还能增进对人工智能工作及增强人类伦理行为的理解。
摘要：
本研究考察了来自OpenAI、Meta、Perplexity、Anthropic、谷歌、Mistral、DeepSeek和xAI的八个著名大语言模型所表达的伦理逻辑。每个模型回答了关于其伦理原则的直接问题，并对五个经典道德困境做出回应。使用结果主义/道义论区分、道德基础理论和科尔伯格道德发展阶段对回答进行分析。各模型的伦理判断大致趋同，通常强调将伤害最小化、公平和情境限定。然而，模型在做决定的意愿、用于捍卫选择的理由以及赋予规则、结果、角色义务和人际考虑的相对权重方面存在差异。它们的自我描述博学、谨慎，并受到对话角色的强烈影响。对自我报告的分析一直是人类心理学和交流研究的核心。我们谨慎地提出，这可以增进我们对人工智能如何工作以及它如何增强人类伦理行为的理解。
英文摘要：
This study examines the expressed ethical logic of eight prominent large language models from OpenAI, Meta, Perplexity, Anthropic, Google, Mistral, DeepSeek, and xAI. Each model answered direct questions about its ethical principles and responded to five classic moral dilemmas. Responses were analyzed using the consequentialist/deontological distinction, Moral Foundations Theory, and Kohlbergs stages of moral development. Across models, ethical judgments were broadly convergent and typically emphasized harm minimization, fairness, and contextual qualification. The models nevertheless differed in their willingness to decide, the rationales used to defend choices, and the relative weight assigned to rules, outcomes, role obligations, and interpersonal considerations. Their self-descriptions were erudite, cautious, and strongly shaped by a conversational persona. The analysis of self-reports has been central to the study of human psychology and communication. We propose, with appropriate cautions, it can enhance our understanding of how artificial intelligence works and how it may be able to augment human ethical behavior
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。
