Considerable advancements have been made in various NLP tasks based on the impressive power of large language models (LLMs) and many NLP applications are deployed in our daily lives. In this work, we challenge the capability of LLMs with the new task of Ethical Quandary Generative Question Answering. Ethical quandary questions are more challenging to address because multiple conflicting answers may exist to a single quandary. We explore the current capability of LLMs in providing an answer with a deliberative exchange of different perspectives to an ethical quandary, in the approach of Socratic philosophy, instead of providing a closed answer like an oracle. We propose a model that searches for different ethical principles applicable to the ethical quandary and generates an answer conditioned on the chosen principles through prompt-based few-shot learning. We also discuss the remaining challenges and ethical issues involved in this task and suggest the direction toward developing responsible NLP systems by incorporating human values explicitly.

翻译：基于大型语言模型（LLMs）的强大能力，各类自然语言处理任务取得了显著进展，众多NLP应用已部署于日常生活。本文通过伦理困境生成式问答这一新任务，挑战LLMs的能力。伦理困境问题因同一困境可能存在多种冲突答案而更具应对难度。我们探索LLMs当前的能力，以苏格拉底哲学的方式（而非如神谕般提供封闭式答案），通过不同视角的审慎交流为伦理困境提供解答。我们提出一种模型，该模型搜索适用于伦理困境的不同伦理原则，并通过基于提示的少样本学习生成基于所选原则的条件化答案。同时，我们讨论了该任务中尚存的挑战与伦理问题，并提出了通过显式融入人类价值观来发展负责任NLP系统的方向。