Users are often overwhelmed by privacy decisions to manage their personal data, which can happen on the web, in mobile, and in IoT environments. These decisions can take various forms -- such as decisions for setting privacy permissions or privacy preferences, decisions responding to consent requests, or to intervene and ``reject'' processing of one's personal data --, and each can have different legal impacts. In all cases and for all types of decisions, scholars and industry have been proposing tools to better automate the process of privacy decisions at different levels, in order to enhance usability. We provide in this paper an overview of the main challenges raised by the automation of privacy decisions, together with a classification scheme of the existing and envisioned work and proposals addressing automation of privacy decisions.

翻译：用户常常被管理个人数据的隐私决策所困扰，这些决策可能发生在网页、移动设备及物联网环境中。这些决策形式多样——例如设置隐私权限或隐私偏好、响应同意请求、进行干预并"拒绝"对个人数据的处理——且每种决策都可能产生不同的法律影响。在所有情况与各类决策中，学界与业界一直在不同层面提出工具以更好地自动化隐私决策过程，从而提升用户体验。本文概述了隐私决策自动化所面临的主要挑战，并提出了一个分类体系，用于梳理现有与已规划的研究工作及方案，这些工作均旨在应对隐私决策的自动化问题。