In the fast-evolving domain of artificial intelligence, large language models (LLMs) such as GPT-3 and GPT-4 are revolutionizing the landscapes of finance, healthcare, and law: domains characterized by their reliance on professional expertise, challenging data acquisition, high-stakes, and stringent regulatory compliance. This survey offers a detailed exploration of the methodologies, applications, challenges, and forward-looking opportunities of LLMs within these high-stakes sectors. We highlight the instrumental role of LLMs in enhancing diagnostic and treatment methodologies in healthcare, innovating financial analytics, and refining legal interpretation and compliance strategies. Moreover, we critically examine the ethics for LLM applications in these fields, pointing out the existing ethical concerns and the need for transparent, fair, and robust AI systems that respect regulatory norms. By presenting a thorough review of current literature and practical applications, we showcase the transformative impact of LLMs, and outline the imperative for interdisciplinary cooperation, methodological advancements, and ethical vigilance. Through this lens, we aim to spark dialogue and inspire future research dedicated to maximizing the benefits of LLMs while mitigating their risks in these precision-dependent sectors. To facilitate future research on LLMs in these critical societal domains, we also initiate a reading list that tracks the latest advancements under this topic, which will be continually updated: \url{https://github.com/czyssrs/LLM_X_papers}.

翻译：在人工智能快速发展的领域，诸如GPT-3和GPT-4等大语言模型正在深刻变革金融、医疗与法律这三个典型领域——它们以依赖专业知识、数据获取困难、高风险及严格监管合规为特征。本综述深入探究了大语言模型在这些高风险领域的方法论、应用、挑战及未来机遇。我们重点阐述了大语言模型在优化医疗诊断与治疗方案、革新金融分析技术、以及完善法律解释与合规策略中的关键作用。同时，我们批判性地审视了大语言模型在这些领域应用的伦理问题，指出当前存在的伦理关切，并强调需要构建透明、公平、稳健且符合监管规范的人工智能系统。通过系统梳理现有文献与实际应用案例，我们展示了大语言模型的变革性影响，并指出跨学科合作、方法论创新及伦理监管的迫切需求。借此视角，我们旨在激发学术对话，推动未来研究致力于最大化大语言模型效益的同时降低其在精准依赖型领域的风险。为促进大语言模型在这些关键社会领域的后续研究，我们还创建了持续更新的专题文献追踪列表：\url{https://github.com/czyssrs/LLM_X_papers}。