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Human-machine co-intelligence through symbiosis in the SMV space

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Abstract

Recent years have witnessed a rapidly-growing research agenda that explores the combined, integrated, and collective intelligence of humans and machines working together as a team. This paper contributes to the same line of research with three main objectives: a) to introduce the concept of the SMV (Symbols-Meaning-Value) space for describing, understanding, and representing human/machine perception, cognition, and action, b) to revisit the notion of human-machine symbiosis, and c) to outline a conceptual framework of human-machine co-intelligence (i.e., the third intelligence) through human-machine symbiosis in the SMV space. By following the principle of three-way decision as thinking in threes, triads of three things are used for building an easy-to-understand, simple-to-remember, and practical-to-use framework. The three elements of the SMV space, namely, Symbols, Meaning, and Value, are closely related to the three basic human/machine functions of perception, cognition, and action, which can be metaphorically described as the seeing-knowing-doing triad or concretely interpreted as the data-knowledge-wisdom (DKW) hierarchy. Human-machine co-intelligence emerges from human-machine symbiosis in the SMV space. As the third intelligence, human-machine co-intelligence relies on and combines human intelligence and machine intelligence, is a higher level of intelligence above either human intelligence or machine intelligence alone, and is greater than the sum of human intelligence and machine intelligence. There are three basic principles of human-machine symbiosis, i.e., unified oneness, division of labor, and coevolution, for nurturing human-machine co-intelligence.

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  1. Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2

    Yiyu Yao

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I would like to thank the Editor-in-Chief Professor Hamido Fujita and the reviewers for their constructive comments and suggestions. This work was partially supported by a Discovery Grant from NSERC, Canada.

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Yao, Y. Human-machine co-intelligence through symbiosis in the SMV space. Appl Intell 53, 2777–2797 (2023). https://doi.org/10.1007/s10489-022-03574-5

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