Responsible AI for Long-term Trustworthy Autonomous Systems (RAILS): Integrating Responsible AI and Socio-legal Governance

社会在自主系统的开发和实施方面取得了巨大的增长，这可以为公民、社区和企业带来巨大的利益。社会福利改善的潜力是巨大的。然而，这种积极的潜力被类似的社会危害潜力所抵消，这些潜在的社会危害是通过诸如自治系统的环境足迹、某些社会经济群体的系统性劣势以及数字鸿沟的巩固等偶然影响。因此，自主系统的推出必须考虑到对社会的责任。这必须包括与社会和受影响的人进行对话，努力在挑战发生之前预测它们，并对它们作出反应。其中一个可预见的挑战是变化对自主系统的影响。自主系统并不是设计用来部署在完全静止状态下的，因为它们不太可能在现实环境中遇到这种情况。它们通常是为不断变化的环境而设计的，比如公共道路，也可能被设计成随着时间的推移而改变自己，比如通过学习能力。不仅如此，这些已部署系统及其运行条件的变化也可能发生在社会变化的背景背景下（例如，其他技术，“黑天鹅”事件，或仅仅是社区的日常运作）。这种变化对系统本身的影响，对系统运行的环境的影响，以及对与之接触的人类的影响，必须被视为负责任的创新方法的一部分。RAILS项目汇集了来自伦敦大学学院、约克大学、利兹大学和牛津大学的团队，他们来自多个学科，旨在应对与自主系统长期运行相关的挑战以及这些系统变化的影响。特别是，我们将探讨责任的概念是如何受到(i)开放式动态环境（随时间变化的情况）和（ii）终身学习系统（即旨在适应环境并随时间“学习”的系统）的影响的。RAILS项目将专注于在不同应用程序中独立的长期自治系统。这些将包括(i)自动驾驶汽车和（ii）无人驾驶飞行器（无人机）等自主机器人系统。RAILS将考虑社会和法律环境，以及技术需求，以评估这些系统是否以及如何以一种负责、负责和值得信赖的方式设计、开发和运行。RAILS项目的总体目标是将负责任的开发原则与治理机制和技术理解结合起来，以创建对自治系统如何适应变化的新理解，如何以负责任和值得信赖的方式部署它们，以及如何通过治理来构建这样的部署以确保问责制和灵活性。

Society is seeing enormous growth in the development and implementation of autonomous systems, which can offer significant benefits to citizens, communities, and businesses. The potential for improvements in societal wellbeing is substantial. However, this positive potential is balanced by a similar potential for societal harm through contingent effects such as the environmental footprint of autonomous systems, systemic disadvantage for some socio-economic groups, and entrenchment of digital divides. The rollout of autonomous systems must therefore be addressed with responsibilities to society in mind. This must include engaging in dialogue with society and with those affected, trying to anticipate challenges before they occur, and responding to them. One such anticipated challenge is the effect of change on autonomous systems. Autonomous systems are not designed to be deployed in conditions of perfect stasis, as they are unlikely to encounter such conditions in real-world environments. They are frequently designed for changing environments, like public roads, and may also be designed to change themselves over time, for instance by means of learning capabilities. Not only that, but these changes in deployed systems and in their operating conditions are also likely to take place against a shifting contextual background of societal alteration (e.g. other technologies, 'black swan' events, or simply the day-to-day operation of communities). The effects of such change, on the systems themselves, on the environments within which they are operating, and on the humans with which they engage, must be considered as part of a responsible innovation approach. The RAILS project brings together a team from UCL and the Universities of York, Leeds and Oxford, from multiple disciplines, with the aim of engaging with the challenges associated with the long-term operation of autonomous systems and the effects of change on these systems. In particular, we will explore how the notion of responsibility is affected by (i) open-ended dynamic environments - situations that change over time, and(ii) lifelong-learning systems - i.e. systems that are designed to adapt themselves to their circumstances and 'learn' over time. The RAILS project will focus on such independent long-term autonomous systems in different applications. These will include (i) autonomous vehicles and (ii) autonomous robot systems such as unmanned aerial vehicles (drones). RAILS will look at social and legal contexts, as well as technical requirements, in order to assess whether and how these systems can be designed, developed, and operated in a way that they are responsible, accountable, and trustworthy. The overall aim of the RAILS project is to bring together responsible development principles with governance mechanisms and technical understanding to create new understandings of how autonomous systems can adapt to change, how they can be deployed in a responsible and trustworthy way, and how such deployment can be framed by governance to ensure accountability and flexibility.