HUMAN-MACHINE COLLECTIVE INTELLIGENCE FOR DECISION SUPPORT: GENERAL VISION

Most of the existing approaches to organize collective work of humans and machines (e.g., in the scope of crowdsourcing or crowd computing) utilize pre-defined workflow specifications. Although strict limitation of the participant’s capabilities pays back in a wide range of applications, creative and organizational abilities of a human in such systems are mostly discarded. Decision support systems, on the other hand, require flexible workflow, because decision making very often is based on interactive and iterative exploration of the problem. The paper discusses a novel class of decision support systems, that are based on an environment, leveraging human-machine collective intelligence, i.e. environment that supports humans and software services jointly working towards a common goal. The distinctive feature of the environment is support for natural self-organization processes in the community of participants (without a pre-defined workflow). The paper outlines general vision of the proposed environment and enumerates a set of foundational technologies and enablers.