We propose a hierarchical framework for collaborative intelligent systems.
This framework organizes research challenges based on the nature of the
collaborative activity and the information that must be shared, with each level
building on capabilities provided by lower levels. We review research paradigms
at each level, with a description of classical engineering-based approaches and
modern alternatives based on machine learning, illustrated with a running
example using a hypothetical personal service robot. We discuss cross-cutting
issues that occur at all levels, focusing on the problem of communicating and
sharing comprehension, the role of explanation and the social nature of
collaboration. We conclude with a summary of research challenges and a
discussion of the potential for economic and societal impact provided by
technologies that enhance human abilities and empower people and society
through collaboration with Intelligent Systems.

我们提出了一个针对协同智能系统的分层框架，运用机器学习辅助，针对交互活动和信息共享的不同层次和挑战，包括传统工程方法和现代机器学习方法，最后探讨了沟通和理解共享、解释和社会协同等问题，总结出未来的研究挑战和为人类社会带来的经济和社会影响。