信任和安全
Trust and Safety
摘要：
澳大利亚的机器人在遵守安全标准和风险管理实践方面有着悠久的历史。本章阐述了机器人技术的信任和安全现状，包括社会的期望，安全管理系统和系统安全，以及确保日益自主的机器人技术安全的新问题和方法。信任和安全的未来将把标准与迭代的、自适应的和响应式的监管和保证方法结合起来，用于机器人、自主系统和人工智能（RAS-AI）的各种应用。机器人技术将需要新的技术和社会方法来实现保证，特别是对于改变游戏规则的创新。用户能够轻松更新算法和软件，这会改变系统的性能，这意味着在部署或销售之前执行的传统机器保证将不再可行。此外，更新频率高意味着需要大量时间的传统认证将不再实用。为了缓解这些困难，可能需要保证的自动化;例如“保证即服务”（ASaas），其中API不断ping RAS-AI以确保遵守各种规则，框架和行为期望。但也有例外，例如在有争议或通信中断的环境中，或在地下或海底采矿中;这些系统需要自己的风险评估和限制。事实上，自我监测已经在一些系统中运行。为了确保未来机器人系统的安全运行，澳大利亚需要投资于RAS-AI保证研究，利益相关者的参与以及持续开发和完善强大的框架，方法，指导方针和政策，以教育和准备其技术开发人员，认证人员和普通民众。
英文摘要：
Robotics in Australia have a long history of conforming with safety standards and risk managed practices. This chapter articulates the current state of trust and safety in robotics including society's expectations, safety management systems and system safety as well as emerging issues and methods for ensuring safety in increasingly autonomous robotics. The future of trust and safety will combine standards with iterative, adaptive and responsive regulatory and assurance methods for diverse applications of robotics, autonomous systems and artificial intelligence (RAS-AI). Robotics will need novel technical and social approaches to achieve assurance, particularly for game-changing innovations. The ability for users to easily update algorithms and software, which alters the performance of a system, implies that traditional machine assurance performed prior to deployment or sale, will no longer be viable. Moreover, the high frequency of updates implies that traditional certification that requires substantial time will no longer be practical. To alleviate these difficulties, automation of assurance will likely be needed; something like 'ASsurance-as-a-Service' (ASaaS), where APIs constantly ping RAS-AI to ensure abidance with various rules, frameworks and behavioural expectations. There are exceptions to this, such as in contested or communications denied environments, or in underground or undersea mining; and these systems need their own risk assessments and limitations imposed. Indeed, self-monitors are already operating within some systems. To ensure safe operations of future robotics systems, Australia needs to invest in RAS-AI assurance research, stakeholder engagement and continued development and refinement of robust frameworks, methods, guidelines and policy in order to educate and prepare its technology developers, certifiers, and general population.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
