Abstract
The paper discusses a novel class of decision support systems, based on an environment, leveraging human-machine collective intelligence. The distinctive feature of the proposed environment is support for natural self-organization processes in the community of participants. Most of the existing approaches for leveraging human expertise in a computing system rely on a pre-defined rigid workflow specification, and those very few systems that try to overcome this limitation sidestep current body of knowledge of self-organization in artificial and natural systems. The paper outlines the general vision of the proposed environment, identifies main challenges that has to be dealt with in order to develop such environment and describes ways to address them. Potential applications of such decision support environment are ubiquitous and influence virtually all areas of human activities, especially in complex domains: business management, environment problems, and government decisions.
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The research is funded by the Russian Science Foundation (project # 19-11-00126).
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Smirnov, A., Ponomarev, A. (2019). Decision Support Based on Human-Machine Collective Intelligence: Major Challenges. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2019 2019. Lecture Notes in Computer Science(), vol 11660. Springer, Cham. https://doi.org/10.1007/978-3-030-30859-9_10
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