The Roots of Collaborative Innovation
There is something fundamental to learn from the brain and biology about new and much more effective forms of processing and computation to develop more effective intelligent systems. The traditional human means of new knowledge is reason, Rational Thinking (RT), the use of order and logic to learn and prosper. Today, human beings realize that, at the same time, they need Emotional Intelligence (EI) and Emotional Creativity (EC) (Goleman, 1995), and the use of open logic and reframing, to create and survive. EI and EC coexist at the same time with RT, sharing the same input environment. Human beings use both Logical Aperture (to get EI and EC, to create and survive) and Logical Closure (to get Rational Thinking, to learn and prosper), both fed by environmental “noise” (or perhaps better, by what human beings call “noise”) (Fiorini, 2014a).
The basic idea of a System Theory (ST) in social science is to solve the classic problem of duality; mind-body, subject-object, form-content, signifier-signified, and structure-agency. ST, therefore, suggests that instead of creating closed categories into binaries (subject-object); the system should stay open so as to allow free flow of process and interactions. In this way the binaries are dissolved. One of the central elements of ST is to move away from the representational system to the non-representation of things. What it means that instead of creating and imposing asymptotic, abstract, mental concepts, which reduce complexity of a materiality by limiting the variations or malleability onto the objects, one should trace the related Network of Things (NoT).
The tracing rather than projecting mental images bring in sight material reality that has been obscured under the universalizing concepts of the past. This perspective opens the door to Actor-Network Theory (ANT) immediately. ANT is a theoretical and methodological approach to social theory where everything in the social and natural worlds exists in constantly shifting networks of relationship. The fundamental aim of ANT is to explore how networks are built or assembled and maintained to achieve a specific objective (Law & Hassard, 1999; Latour, 2005; Yaneva, 2009; Carroll, 2014).