Assuring Responsibility for Trustworthy Autonomous Systems

自主系统，如医疗系统、自主空中和道路车辆、制造和农业机器人，有望扩展和扩大人类的能力。但是，只有当人们信任围绕其设计、开发和部署的人工流程时，它们的好处才会得到利用。使设计人员、工程师、开发人员、监管机构、运营商和用户能够追踪和分配自主系统的决策、行动、故障和结果的责任，对于这种信任生态系统至关重要。如果一辆自动驾驶汽车做出了影响到你的行为，你会想知道谁应该对此负责，以及补救的渠道是什么。如果你是一名在临床环境中使用自主系统的医生，你会想要了解你、医疗机构和系统开发者之间的责任分配。设计师和工程师需要明确他们的责任，以及这些责任何时转移到决策网络中的其他代理。制造商需要了解他们将承担什么法律责任。实现这种透明度的机制不仅将为所有利益相关者提供保证，还将增加决策者的清晰度、信心和能力。该研究项目是一项跨学科的工作计划——借鉴了工程学、法学和哲学等学科——最终形成了一种精确实现责任追踪和分配的方法。通过“追踪责任”，我们指的是将自主系统的决策或结果追踪到设计师、工程师或操作员的决策，并了解导致结果的原因的过程。通过“分配责任”，我们指的是在整个生命周期中将角色责任分配给不同的主体，并提前确定谁将对不同的系统决策和结果承担法律责任和道德责任。这种方法将促进按设计负责和按生命周期负责。在实践中，AS的决策和结果的责任追踪和分配是非常复杂的。系统的复杂性以及运行环境的不断变化和不可预测性使得个体的因果关系难以区分。当我们将任务委托给需要人类道德判断和合法行为的系统时，它也会产生潜在的道德和法律责任缺口。系统越复杂和自治，保证在追踪和分配责任中扮演的角色就越重要，特别是在技术和组织复杂的环境中。该研究项目正面解决了这些挑战。首先，我们澄清了责任的基本概念，不同类型的责任，涉及的不同主体，以及“责任差距”的产生和如何解决。其次，我们建立在高风险系统的技术保证中使用的技术基础上，在不确定性和动态性的背景下推理责任，因此不可预测的社会技术环境。总之，这些工作链为设计责任和贯穿生命周期的责任方法论提供了基础，可以在实践中被广泛的涉众使用。责任保证将被实现，不仅确定哪些代理在整个生命周期中以何种方式对哪些结果负责，并解释如何实现这种识别，而且还确定为什么这种跟踪和责任分配是合理的和完整的。

Autonomous systems, such as medical systems, autonomous aerial and road vehicles, and manufacturing and agricultural robots, promise to extend and expand human capacities. But their benefits will only be harnessed if people have trust in the human processes around their design, development, and deployment. Enabling designers, engineers, developers, regulators, operators, and users to trace and allocate responsibility for the decisions, actions, failures, and outcomes of autonomous systems will be essential to this ecosystem of trust. If a self-driving car takes an action that affects you, you will want to know who is responsible for it and what are the channels for redress. If you are a doctor using an autonomous system in a clinical setting, you will want to understand the distribution of accountability between you, the healthcare organisation, and the developers of the system. Designers and engineers need clarity about what responsibilities fall on them, and when these transfer to other agents in the decision-making network. Manufacturers need to understand what they would be legally liable for. Mechanisms to achieve this transparency will not only provide all stakeholders with reassurance, they will also increase clarity, confidence, and competence amongst decision-makers. The research project is an interdisciplinary programme of work - drawing on the disciplines of engineering, law, and philosophy - that culminates in a methodology to achieve precisely that tracing and allocation of responsibility. By 'tracing responsibility' we mean the process of tracking the autonomous system's decisions or outcomes back to the decisions of designers, engineers, or operators, and understanding what led to the outcome. By 'allocating responsibility' we mean both allocating role responsibilities to different agents across the life-cycle and working out in advance who would be legally liable and morally responsible for different system decisions and outcomes once they have occurred. This methodology will facilitate responsibility-by-design and responsibility-through-lifecycle. In practice, the tracing and allocation of responsibility for the decisions and outcomes of AS is very complex. The complexity of the systems and the constant movement and unpredictability of their operational environments makes individual causal contributions difficult to distinguish. When this is combined with the fact that we delegate tasks to systems that require ethical judgement and lawful behaviour in human beings, it also gives rise to potential moral and legal responsibility gaps. The more complex and autonomous the system is, the more significant the role that assurance will play in tracing and allocating responsibility, especially in contexts that are technically and organisationally complex. The research project tackles these challenges head on. First, we clarify the fundamental concepts of responsibility, the different kinds of responsibility in play, the different agents involved, and where 'responsibility gaps' arise and how they can be addressed. Second, we build on techniques used in the technical assurance of high-risk systems to reason about responsibility in the context of uncertainty and dynamism, and therefore unpredictable socio-technical environments. Together, these strands of work provide the basis for a methodology for responsibility-by-design and responsibility-through-lifecycle that can be used in practice by a wide range of stakeholders. Assurance of responsibility will be achieved that not only identifies which agents are responsible for which outcomes and in what way throughout the lifecycle, and explains how this identification is achieved, but also establishes why this tracing and allocation of responsibility is well-justified and complete.