The past decade has observed a significant advancement in AI with deep learning-based models being deployed in diverse scenarios, including safety-critical applications. As these AI systems become deeply embedded in our societal infrastructure, the repercussions of their decisions and actions have significant consequences, making the ethical implications of AI deployment highly relevant and essential. The ethical concerns associated with AI are multifaceted, including challenging issues of fairness, privacy and data protection, responsibility and accountability, safety and robustness, transparency and explainability, and environmental impact. These principles together form the foundations of ethical AI considerations that concern every stakeholder in the AI system lifecycle. In light of the present ethical and future x-risk concerns, governments have shown increasing interest in establishing guidelines for the ethical deployment of AI. This work unifies the current and future ethical concerns of deploying AI into society. While we acknowledge and appreciate the technical surveys for each of the ethical principles concerned, in this paper, we aim to provide a comprehensive overview that not only addresses each principle from a technical point of view but also discusses them from a social perspective.

翻译：过去十年间，人工智能在深度学习模型的推动下取得了显著进展，这些模型已被部署于包括安全关键型应用在内的多样化场景中。随着人工智能系统深度融入社会基础设施，其决策与行为产生的连锁反应具有重大影响，这使得人工智能部署的伦理问题变得高度相关且至关重要。人工智能所涉及的伦理关切是多维度的，涵盖公平性、隐私与数据保护、责任与问责、安全性与鲁棒性、透明度与可解释性以及环境影响等一系列挑战性议题。这些原则共同构成了人工智能伦理考量的基础，关系到人工智能系统生命周期中的所有利益相关者。鉴于当前伦理问题及未来存在的极端风险（x-risk）隐忧，各国政府已展现出对制定人工智能伦理部署准则的日益增长的兴趣。本研究将当前及未来人工智能社会部署中的伦理关切进行了系统性整合。尽管我们认可并重视针对各项伦理原则的技术性综述，但本文旨在提供一个全面的概览，不仅从技术视角剖析各项原则，更从社会维度展开深入探讨。