We focus on the development of AIs which live in lifelong symbiosis with a human. The key prerequisite for this task is that the AI understands - at any moment in time - the personal situational context that the human is in. We outline the key challenges that this task brings forth, namely (i) handling the human-like and ego-centric nature of the the user's context, necessary for understanding and providing useful suggestions, (ii) performing lifelong context recognition using machine learning in a way that is robust to change, and (iii) maintaining alignment between the AI's and human's representations of the world through continual bidirectional interaction. In this short paper, we summarize our recent attempts at tackling these challenges, discuss the lessons learned, and highlight directions of future research. The main take-away message is that pursuing this project requires research which lies at the intersection of knowledge representation and machine learning. Neither technology can achieve this goal without the other.

本研究聚焦于开发与人类共生的AI，并探讨了该任务所面临的挑战，包括处理用户情境、实现机器学习下的生涯上下文识别、通过持续的双向交互来保持AI与人类对世界的表达方式的一致性等。作者对这些挑战的尝试总结了经验，并强调了今后的研究方向，认为该项目需要知识表示和机器学习之间的交叉研究。

终身个人上下文识别