This paper explores the integration of human-like emotions and ethical
considerations into Large Language Models (LLMs). We first model eight
fundamental human emotions, presented as opposing pairs, and employ
collaborative LLMs to reinterpret and express these emotions across a spectrum
of intensity. Our focus extends to embedding a latent ethical dimension within
LLMs, guided by a novel self-supervised learning algorithm with human feedback
(SSHF). This approach enables LLMs to perform self-evaluations and adjustments
concerning ethical guidelines, enhancing their capability to generate content
that is not only emotionally resonant but also ethically aligned. The
methodologies and case studies presented herein illustrate the potential of
LLMs to transcend mere text and image generation, venturing into the realms of
empathetic interaction and principled decision-making, thereby setting a new
precedent in the development of emotionally aware and ethically conscious AI
systems.

本文探讨了如何将类人情感和伦理考虑整合到大型语言模型（LLM）中，并通过协作式 LLM 对八种基本人类情感进行建模，以及通过自我监督学习算法与人类反馈指导在 LLM 中嵌入潜在的伦理维度。利用该方法，LLMs 能够进行自我评估和调整以符合伦理准则，并提高其生成与情感共鸣和伦理一致的内容的能力。所提出的方法和案例研究展示了 LLMs 超越纯文本和图像生成，进入共情互动和有原则决策领域的潜力，并在情感意识和伦理意识的 AI 系统发展中树立了新的范例。