Understanding Collective Intelligence: Investigating the Role of Collective Memory, Attention, and Reasoning Processes

As society has come to rely on groups and technology to address many of our most challenging problems, there is a growing need to understand how technology-enabled, distributed, and dynamic collectives can be designed to solve a wide range of problems over time in the face of complex and changing environmental conditions — an ability reflected in “collective intelligence.” We describe recent research on the Transactive Systems Model of Collective Intelligence (TSM-CI) that integrates literature from diverse areas of psychology to conceptualize the underpinnings of collective intelligence. The TSM-CI model articulates the development and mutual adaptation of transactive memory (TMS), transactive attention (TAS), and transactive reasoning (TRS) systems that together support the emergence and maintenance of collective intelligence. We also review related research on computational indicators of transactive system functioning based on collaborative process behaviors that enable agent-based teammates to diagnose and potentially intervene to address developing issues. We conclude by discussing future directions in developing the TSM-CI to support research on developing Collective Human-Machine Intelligence (COHUMAIN) and to identify ways to design technology to enhance it."}]}As society has come to rely on groups and technology to address many of our most challenging problems, there is a growing need to understand how technology-enabled, distributed, and dynamic collectives can be designed to solve a wide range of problems over time in the face of complex and changing environmental conditions — an ability reflected in “collective intelligence.” We describe recent research on the  Systems Model of Collective Intelligence (TSM-CI) that integrates literature from diverse areas of psychology to conceptualize the underpinnings of collective intelligence. The TSM-CI model articulates the development and mutual adaptation of  memory (TMS),  attention (TAS), and  reasoning (TRS) systems that together support the emergence and maintenance of collective intelligence. We also review related research on computational indicators of  system functioning based on collaborative process behaviors that enable agent-based teammates to diagnose and potentially intervene to address developing issues. We conclude by discussing future directions in developing the TSM-CI to support research on developing Collective Human-Machine Intelligence (COHUMAIN) and to identify ways to design technology to enhance it.