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：用户往往因管理个人数据的隐私决策而感到不堪重负，这些决策可能发生在网络、移动及物联网环境中。此类决策形式多样——例如设定隐私权限或隐私偏好、回应同意请求、干预并“拒绝”他人处理个人数据——且每种决策可能产生不同的法律影响。针对所有情形与决策类型，学界与业界已提出多种工具，旨在不同层面更好地实现隐私决策过程的自动化，以提升可用性。本文概述了隐私决策自动化的主要挑战，并提出了一个分类框架，用于梳理现有及规划中的自动化隐私决策相关研究与方案。