Whilst it’s true that the rise Artificial Intelligence threatens industries and jobs alike, it also presents an opportunity for humans and teams to embrace the new paradigm by staying one step ahead and making themselves smarter and more capable in harnessing collective intelligence. The term collective intelligence refers to the resulting knowledge or wisdom that ensues when many agents or individuals are involved in a group and where this type of ‘intelligence’ cannot exist through an individual endeavour. It is therefore important that in the face of tectonic shifts in technology and the rise of intelligent machines coupled with the threat of automation; teams and humans embrace a form of ‘swarming’ in order to not only future proof themselves but create the right type of environment to achieve outcomes that could not be reached through individual pursuits. In this article, I refer to various examples of how Nature’s team achieve this ‘swarm intelligence’ and appropriate how these can be achieved in the organisational setting through Bioteaming.
For billions of years, collective intelligence and swarm behaviour has been evident in Nature where social species like Bees work together to make better decisions such as when they want to setup a new colony. In the context of Bees, a few hundred scout bees will journey into different directions to look for potential nest locations. Once identified, the scouts perform a waggle dance which functions like a one way broadcast to share the direction and distance to the new nest site locations with other members of the colony. Different scouts may have attempted to pull the swarm towards or away from their preferred direction and eventually the colony decides as a group which scout to follow, making a decision no individual bee could have ever made on their own. This use of an effective ‘collective brain’ is also evident in ant colonies where millions of them come together to create what is perceived as a complex two way highway buzzing with traffic. Dr. Couzin a mathematical biologist at Princeton University and the University of Oxford notes that Army Ants, in particular, “build the bridges with their living bodies….”they build them up if they’re required, and they dissolve if they’re not being used”. This shows how ants are able to optimise to its environment, another fsacinating display of scaling and adaptability.
The examples of the Bees and Ants herewith are great examples of stigmergy as a mechanism for indirect coordinator between agents or actions, something that human teams must embrace to nurture collective intelligence. To recap, stigmergy is a form of self organistion where it produces complex, seemingly intelligent structures without the need for any planning, control or even direct communication between the agents. As such, it supports efficient collaboration between extremely simple agents, who lack any memory, intelligence or even individual awareness of each other.
So how do humans and teams achieve the same degree of super intelligence that is exhibited by group interaction from the social insects? How do teams achieve a level of amplification that enables them to make better decisions, predictions, estimations and forecasts and as a result – achieve outcomes quicker and in a more effective manner? Ultimately, the ability to adapt and solve problems are all ascribed to intelligence as a collective capacity and it must be nurtured and deployed strategically.
To contextualise and formulate this for humans and teams, its worthy to note that the interactions that nurture collective intelligence in Nature’s teams are governed by fundamentally simple rules. The culmination and adherence of these rules lead to the emergence of complex and subsequent autonomous and intelligent behaviour. This then brings on identification of the optimal solution or a resulting type of ‘swarm intelligence‘. Ants for example use antennas to asses if it makes contact with another ant and turns around and slows down if so to avoid collisions.
A study into Morman crickets found that their collective movement causes the crickets to form vast swarms. Dr Couzin observed that “they’re trying to attack the crickets who are ahead, and they’re trying to avoid being eaten from behind” which gives insight into agility and the ability to act like a collective mind. Therefore, for humans and teams, it’s important to understand that in settings where you are working with project members that span different departments, geographies and cultural varieties – the best way to leverage everyone’s capabilities is to implement a framework that nurtures shared decision making in combination with collaborative style effective communication.
Bioteams exhibit elements of swarm intelligence in group settings by defining themselves in terms of transformations, not outputs. This is a contrast to the traditional model of teamwork wherein activities, tasks or outputs are explicitly defined. If a team wishes to embrace collective intelligence and swarm behaviours, they should define themselves in terms of the transformations they wish to make on their network components. Network components are the sub of internal and external stakeholders as well as processes, systems and people capabilities intrinsic to the enterprise. By doing this, it will be possible to enable humans to think together as super intelligent systems that connect groups of other individuals from all areas of expertise together over computer networks and virtual technologies, thereby enabling everyone to think together as a system that emulates the intelligence that emerges from swarms in Nature.
A critical factor in creating the right technological and process mix for collective and swarm intelligence in enterprises and human teams is to traverse the use of polls and surveys (which have been the most common method for harnessing the intelligence of human groups for several decades) and focusing on moving towards real time communication, innovation frameworks and methodologies that inspire teams under the tenets of distributed leadership. These practices should be underpinned by a few set of rules that support a collaborative orientation, as referenced in this article.
Ultimately, as technologies, people capabilities and process continually coalesce; its quite clear that Bioteaming like models of distributed, collaborative leadership and teamwork will ultimately define the evolution of teams within organisations. Dr R Meredith Belbin, regarded as the father of team-role theory, prophesises that teams will take more biological forms as they learn from a “diminuitive masterclass” of sical insects such as bees, ants and terminates. More on that, can be read in this article.
About Max Bhanabhai
Max Bhanabhai is a bioteaming practitioner, author, strategic innovation and change management consultant. Max collaborates on Bioteams with Ken Thompson (The Bumble Bee). For more information on this important topic checkout Ken’s book – “A Systematic Guide to High Performing Teams (HPTs)“
- Thompson, K. (2008). Bioteams. 1st ed. Tampa, Fla.: Meghan-Kiffer Press, part 3.
- Lilianricaud.com. (2019). Collective Intelligence in Nature: ants cities and stigmergy – Web Strategy – Lilian Ricaud. [online] Available at: http://www.lilianricaud.com/web-strategy/collective-intelligence-in-nature-ants-cities-and-stigmergy/ [Accessed 11 Dec. 2019].
- Warnock, C. (2019). The Predictive Power of Artificial Swarm Intelligence – SU Blog. [online] Su.org. Available at: https://su.org/blog/can-humans-use-artificial-swarm-intelligence-to-make-smarter-faster-decisions/amp/ [Accessed 11 Dec. 2019].
- Zimmer, C. (2019). From Ants to People, an Instinct to Swarm. [online] Nytimes.com. Available at: https://www.nytimes.com/2007/11/13/science/13traff.html [Accessed 11 Dec. 2019].
- Rosenberg, L. (2019). How collective intelligence helps organizations move past hierarchical leadership structures. [online] The Next Web. Available at: https://thenextweb.com/insider/2015/12/29/how-collective-intelligence-helps-organizations-move-past-hierarchical-leadership-structures/ [Accessed 11 Dec. 2019].