Abstract
This article explores the nexus where purposeful individual-driven collective action, what is called organizational leadership, interacts with collective intelligence and agency. Based on recent numerical models from complex network theory and empirical studies of collective dynamics in social biology, it describes how intelligent collective agency forms around three order parameters: expectancy alignment, instrumentality inside the collective, and a subjective belief by individual agents in the generalized trustworthiness of other members of a collective. When the value of one or more of these scaling metrics becomes dynamically stable, fractal structures in the collective provide useful information to individuals that informs their choices during interactions including leadership activities. The theory contributes fifteen testable assertions that if supported empirically suggest fruitful ways that new information technology applications could enhance organizational effectiveness.
Highlights
This article proposes a new conceptual model of emergent collective intelligent agency (CIA)
When the scaling dynamics described in prior sections are considered from the point-of-view of an individual who is trying to make sense of his or her broader social environment, the interpretive conundrum faced by agents is that current information signals that may be relevant to future states can only be inferred by observing persistent coarse-grain patterns in the decision-states of other agents as these were observed during prior time steps
The complexity dynamics of these social networks underlie information processing mechanisms that can emerge as CAI during complex organizing in human organizations
Summary
This article proposes a new conceptual model of emergent collective intelligent agency (CIA). The central contributions of this article are the assertions that suggest that information relevant to individuals is embedded in three distinct scaling structures which interact along distinct degrees of freedom It conjectures that information about each of these types can be quantified in relation to a different order parameter: alignment of agent attention vis-avis the ecosystem, instrumental momentum among the agents within the organization who are associated with that organization’s properties, and the level of trustworthiness of others that is assumed by agents within the organization. The CIA model assumes that each agent observes, decodes and uses information along each of these degrees of freedom to inform the evolving and interdependent decision states of interacting agents as events unfold Exposing these information processing conditions in human organizations suggests opportunities for future ICT research and development
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