In a world where change is the only constant, we must design for adaptability. This is also true for social systems.
In a highly connected, complex and uncertain world, we lose all ability to predict future events. Indeed, connectedness creates complexity and complexity bring uncertainty as events do not have their sources in easily identifiable causes anymore, but in a web of intricate relationships that mutually influence each other. As we are now entering in uncharted territory, and not knowing the nature of the changes that are coming, we must somehow include a capacity for resilience on one hand, and a capacity to exercise trust as a fundamental element of social relationships on the other hand. As the viability of social systems depends on their ability to adapt and co-evolve with the ever-changing social environment, resolving the questions of adaptability and trust is paramount to our survival as a human species. Like Charles Darwin states: “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change”. Now, how are we going to engage into that transition is a question that remains open. “In the long history of human kind (and animal kind, too) those who learned to collaborate and improvise most effectively have prevailed”.
We propose complexity theory as a way to tackle the challenge of adaptability in human society. Human society being a complex environment, and complex systems being optimized for adaptability and flexibility, complexity theory is a natural candidate to provide useful insights. Therefore, we aim to explore how social trust can be understood through the lens of complex systems and be applied to human society as the bedrock for social interactions. Trust being a firm belief in the integrity, ability and reliance of a person, trusting others is a willingness to enter into a position of dependence and vulnerability toward those who are trusted. Trusting others may yield various results within a wide dynamic range: from the experience of negative emotions such as being abused, betrayed and deceived, to the experience of positive ones such as meeting positive outcomes. Trust has thus at its core two interrelated aspects: risks and opportunities and these two elements need to be taken into account. Trust being also a complex subjective perception, there is simply no way to reduce trust to simple objective metrics. Yet, the experience of emotions being irrational by nature, it can nevertheless lead to behaviors that are themselves rational and predictable to some degree.
With this in mind, we investigate how a coherent structure can emerge out of the multitude of preferential interactions. Complex systems such as ecosystems do not evolve under a top down hierarchy, instead their structure result from the dynamics between the micro and macro levels. At the micro level, discrete units systematically avoid friction in favor of the path of least resistance. At the macro level, the state of symbiosis is most of the time prefered over competition as synergistic relationships are less energy consuming. Transposing these dynamics to human society, at the micro or individual level, we assume that people naturally avoid negative emotions in favor of positive ones. At the macro or collective level, we explore how social emotions and intertwined interests can make the pursuit of narrow advantages systematically less desirable than maintaining synergistic relationships. Indeed, trusted relationships are hard to build, easy to lose with a breach of confidence, and even harder to rebuild due to the memory of past interactions that are distributed in the social ecosystem. Trusted relationships being sometimes a priceless social asset, free riding, though being allowed, comes at the cost of facing the risk to lose credibility and therefore access to valuable social clusters.
The three core elements of the social ecosystem would be: (1) a fractal shape to allow trust to be scaled up through the interconnection of small social clusters, (2) an emergent structure supported by systematic incentives for people to reach and maintain synergistic behaviors, and (3) self-adaptive networks that dynamically translate the state of synergy among the social ecosystem.
The model would translate as a risk-aware recommender system where people engage their credibility toward their peers. This recommender system anchored in qualitative relationships is expected to lead to the formation of transversal knowledge networks operating within, across, and beyond social organizations. It would provide the greatest alignment of human resources in the network that coincide with the highest levels of trustworthiness, while capacity to make and execute decisions is maintained at every level of the fractal’s heterarchy. This general purpose model, inspired by the way ecosystems operate, could be applied to every domain of society and is expected to positively impact social engagement, to foster a more resonant leadership, and to deploy collective intelligence at scale while being more flexible, robust and resilient toward change.
At the research level, and based on complexity theory, we aim to open the discussion for a new organizational model adapted to a fully networked society. Self-organization being a major property of complex systems, we aim to explore how to create the capacity to tackle exponential challenges with exponential solutions as a way to be more responsive to the global risks facing humanity.
At the practical level, we aim to develop a new online environment that systematically promotes qualitative social relationships based on trust, recognition and reciprocity. We further envision the model to become a backbone for additional social innovations, from the build up of the commons, to swarm intelligence and collective decision making.