This study addresses ethical issues surrounding Large Language Models (LLMs) within the field of artificial intelligence. It explores the common ethical challenges posed by both LLMs and other AI systems, such as privacy and fairness, as well as ethical challenges uniquely arising from LLMs. It highlights challenges such as hallucination, verifiable accountability, and decoding censorship complexity, which are unique to LLMs and distinct from those encountered in traditional AI systems. The study underscores the need to tackle these complexities to ensure accountability, reduce biases, and enhance transparency in the influential role that LLMs play in shaping information dissemination. It proposes mitigation strategies and future directions for LLM ethics, advocating for interdisciplinary collaboration. It recommends ethical frameworks tailored to specific domains and dynamic auditing systems adapted to diverse contexts. This roadmap aims to guide responsible development and integration of LLMs, envisioning a future where ethical considerations govern AI advancements in society.

本研究探讨了人工智能领域中大型语言模型（LLMs）的伦理问题。它讨论了LLMs和其他人工智能系统所面临的常见伦理挑战，如隐私和公平，以及LLMs特有的伦理挑战，如幻觉、可验证的问责和解码审查复杂性。该研究强调了解决这些复杂性的必要性，以确保问责制、减少偏见并增强LLMs在塑造信息传播方面所扮演的重要角色的透明度。它提出了缓解策略和LLM伦理的未来发展方向，主张跨学科合作。该研究建议针对特定领域制定伦理框架，并根据不同环境调整动态审计系统。这一路线图旨在引导负责任地开发和整合LLMs，设想一个以伦理考虑为基础的人工智能进步的未来社会。

LLM伦理导航：进展、挑战和未来方向