We develop the idea of collective intelligence by analysing a range of factors hindering the effectiveness of interactive cognitive agents. We give insights into how to explore the potential of collectives across different cognitive systems (human, animal and machine) and research areas. The endeavour is to bridge the different research disciplines in which collective intelligence might occur and apply the studies of intelligence in AI to other fields, thereby cross-fertilising diverse areas of study ranging from business and management to social sciences and fundamental biology.

The dynamics and characteristics behind intelligent cognitive systems lie at the heart of understanding, and devising, successful solutions to a variety of multiagent problems. Despite the extant literature on collective intelligence, important questions like “how does the effectiveness of a collective compare to its isolated members?” and “are there some general rules or properties shaping the spread of intelligence across various cognitive systems and environments?” remain somewhat of a mystery. In this paper we develop the idea of collective intelligence by giving some insight into a range of factors hindering and influencing the effectiveness of interactive cognitive systems. We measure the influence of each examined factor on intelligence independently, and empirically show that collective intelligence is a function of them all simultaneously. We further investigate how the organisational structure of equally sized groups shapes their effectiveness. The outcome is fundamental to the understanding and prediction of the collective performance of multiagent systems, and for quantifying the emergence of intelligence over different environmental settings.