Collaborative Systems Change and Collective Intelligence

 




Pranav Gupta and Anita Woolley have generated a framework for collective intelligence that informs possibilities for socio-technical efforts that bridge artificial intelligence and human decision-making.  Their framework, a Transactive Systems Model of Collective Intelligence (TSM-CI), uses theory and evidence from human psychological science to define intelligence and posit a plausible understanding of collective intelligence, its components, processes, and measurable constructs (full citations below).

From their work we learn that any intelligent system (like a human) manages three primary functions - memory, attention, and reasoning – to achieve goals.  The basic functions underlying intelligence become transactive in a collective intelligence framework indicating that by combining and exchanging memory, attention, and reasoning groups improve their chances of achieving shared goals.  Gupta and Wooley advise that optimal combining and exchanging of memory, attention, and reasoning and consequent intelligent behavior will occur and be sustained only when members of groups perceive an advantage to collaborating rather than working independently.

Ahhh, collaboration.  

While reading their work I remembered related ideas from other fields addressing human challenges.

The field of knowledge management, for example, has generated myriad models and tools for unearthing, archiving, and activating what is known in human groups.

The field of implementation science has amassed numerous frameworks and tools for connecting human knowing and doing, earlier in service of fidelity to known plans and more recently toward optimizing what is known, what is possible, and what is desirable in unique contexts.

From the field of participatory and developmental evaluation Michael Quinn Patton has noted that “we don’t know it until we all know it together,” implying that groups working toward shared goals benefit from shared knowledge, attention, and reasoning.

The field of systems change attempts to coordinate coherent and desired change among the interconnected elements of visible and not-so-visible systems. Adjacent fields of systems thinking and systems modeling provide tools that support participatory and joint knowledge, attention, and reasoning processes, leading me to believe that Gupta and Woolley’s work is relevant for collaborative processes in systems change initiatives.  I’d like to know more about the practices and tools people use to foster shared knowledge, shared attention, and shared reasoning in systems change related to eliminating persistent injustices.



Gupta, P., & Woolley, A. W. (2021, September). Articulating the role of artificial intelligence in collective intelligence: A transactive systems framework. In Proceedings of the human factors and ergonomics society annual meeting (Vol. 65, No. 1, pp. 670-674). Sage CA: Los Angeles, CA: SAGE Publications.

Woolley, A. W., & Gupta, P. (2023). Understanding Collective Intelligence: Investigating the Role of Collective Memory, Attention, and Reasoning Processes. Perspectives on Psychological Science, 17456916231191534.

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