As AI systems become more advanced, companies and regulators will make
difficult decisions about whether it is safe to train and deploy them. To
prepare for these decisions, we investigate how developers could make a 'safety
case,' which is a structured rationale that AI systems are unlikely to cause a
catastrophe. We propose a framework for organizing a safety case and discuss
four categories of arguments to justify safety: total inability to cause a
catastrophe, sufficiently strong control measures, trustworthiness despite
capability to cause harm, and deference to credible AI advisors. We evaluate
concrete examples of arguments in each category and outline how arguments could
be combined to justify that AI systems are safe to deploy.

AI 系统的安全性是一个重要的考量，因此作者提出了一个结构化的理由框架，包含四个类别的论证，以证明 AI 系统在训练和部署过程中不太可能引发灾难，并提到控制措施的强度、即使可能造成伤害也是可信的、以及可信的 AI 顾问的权威等内容。

安全案例：为先进人工智能系统提供安全证明

Safety Cases: Justifying the Safety of Advanced AI Systems

An overview of the process to develop a safety case for an autonomous robot
deployment on a nuclear site in the UK is described and a safety case for a
hypothetical robot incorporating AI is presented. This forms a first step
towards a deployment, showing what is possible now and what may be possible
with development of tools. It forms the basis for further discussion between
nuclear site licensees, the Office for Nuclear Regulation (ONR), industry and
academia.

描述了一种在英国核电站部署自主机器人时开发安全案例的过程概述，并呈现了一个包含人工智能的假想机器人的安全案例，为核电站执照持有人、核能监管局（ONR）、工业界和学术界之间的进一步讨论提供基础。

用于英国核环境中的自主系统安全案例

Autonomous Systems' Safety Cases for use in UK Nuclear Environments

Modern systems are designed to operate in increasingly variable and uncertain
environments. Not only are these environments complex, in the sense that they
contain a tremendous number of variables, but they also change over time.
Systems must be able to adjust their behaviour at run-time to manage these
uncertainties. These self-adaptive systems have been studied extensively. This
paper proposes a definition of a safety-critical self-adaptive system and then
describes a taxonomy for classifying adaptations into different types based on
their impact on the system's safety and the system's safety case. The taxonomy
expresses criteria for classification and then describes specific criteria that
the safety case for a self-adaptive system must satisfy, depending on the type
of adaptations performed. Each type in the taxonomy is illustrated using the
example of a safety-critical self-adaptive water heating system.

该论文提出了一个安全关键的自适应系统的定义并描述了一套分类自适应系统中的不同类型的适应，并根据它们对系统安全和系统安全案例的影响提出了可分类的标准。分类中的每一种类型都使用安全关键的自适应热水系统的例子进行说明。