We are at the beginning of a new age in which artificial entities will perform significant amounts of high-level cognitive processing rivaling and even surpassing human thinking. The future belongs to those who can best collaborate with artificial cognitive entities achieving a high degree of cognitive augmenta-tion. However, we currently lack theoretically grounded fundamental metrics able to describe human or artificial cognition much less augmented and combined cognition. How do we measure thinking, cognition, information, and knowledge in an implementation-independent way? How can we tell how much thinking an artificial entity does and how much is done by a human? How can we measure the combined and possible even emergent effect of humans working together with intelligent artificial entities? These are some of the challenges for research-ers in this field. We first define a cognitive process as the transformation of data, information, knowledge, and wisdom. We then review several existing and emerging information metrics based on entropy, processing effort, quantum physics, emergent capacity, and human concept learning. We then discuss how these fail to answer the above questions and provide guidelines for future re-search.
翻译:我们正处于一个新时代的开始,在这个时代,人造实体将进行大量高层次的认知处理,对抗甚至超越人类的思维。未来属于那些能够最好地与人造认知实体合作,实现高度认知增强的人造认知实体。然而,我们目前缺乏能够描述人类或人工认知的具有理论基础的基本衡量标准,这种基本衡量标准远没有那么扩大和结合。我们如何以独立执行的方式衡量思维、认知、信息和知识?我们如何以独立执行的方式衡量思维、认知、信息和知识?我们如何判断人造实体的思维能力,以及人类做了多少工作?我们如何衡量人类与智能人工实体合作的合并效应和潜在效应?这是研究者在这一领域面临的一些挑战。我们首先将认知进程定义为数据、信息、知识和智慧的转变。然后我们审查几个基于昆虫、处理努力、量子物理学、新兴能力和人类概念学习的现有和新出现的信息衡量标准。然后我们讨论这些方法如何无法回答上述问题并为未来再研究提供指导方针。