Collaborative AI systems (CAISs) aim at working together with humans in a shared space to achieve a common goal. This critical setting yields hazardous circumstances that could harm human beings. Thus, building such systems with strong assurances of compliance with requirements, domain-specific standards and regulations is of greatest importance. Only few scale impact has been reported so far for such systems since much work remains to manage possible risks. We identify emerging problems in this context and then we report our vision, as well as the progress of our multidisciplinary research team composed of software/systems, and mechatronics engineers to develop a risk-driven assurance process for CAISs.

翻译：合作性AI系统(CAIS)的目标是在共同空间与人类合作,以实现一个共同目标,这一关键环境会产生危害人类的危险情况,因此,在建立这种系统时,以严格保证符合要求、具体领域标准和条例,是最重要的,迄今为止,由于在管理可能的风险方面仍有许多工作要做,因此这类系统的影响很少。我们查明了这方面的新问题,然后报告了我们的愿景,以及由软件/系统以及机械工程师组成的多学科研究小组的进展情况,以便为CAIS开发一种风险驱动的保证程序。