Il n’y a pas de définition ou de modèle unique de la mutualisation. Pour moi, il s’agit d’une manière de penser, de travailler en collaboration. Les fondements sont toutefois toujours les mêmes : l’action de partager ou de mettre en commun quelque chose. Bien entendu, dans la mutualisation, il y a l’idée de « mutuel », il faut regrouper plusieurs individus ou organismes dans un projet commun. Chaque partie prenante retire donc des bénéfices de cette collaboration, même si ces bénéfices ne sont pas nécessairement répartis également pour chaque partenaire. L’idée n’est pas de prendre des biens et de les diviser en deux. Il s’agit plutôt de mettre en commun des ressources mutuelles ensemble. La somme des ressources impliquées rend le projet plus fort.
The gig economy has become a hot topic. The term itself derives from the world of entertainment, particularly live music, where performers striving for recognition hope to get a few ‘gigs’ – i.e. short-term and sporadic opportunities for paid employment, with the understanding that such engagements are limited and without any future obligation on either party – employer or employee. This seemingly gives both parties significant autonomy, albeit not in equal measure. I show how key aspects of Zygmunt Bauman’s work prepare us for an understanding and appreciation of the gig economy, and other more extensive ramifications; particularly those exemplified in the success of the Open Source model, and its potential – or not – to provide the basis for new institutional forms appropriate and acceptable for our current context.
Some call it the fourth industrial revolution. The age of the Human-supported assembly line that began with Ford is long gone. This industrial revolution won’t be marked by a monstrous industrial machine supported by a robust middle-class, trained and molded by a public school system. This industrial revolution will be marked by machine learning, big data, and artificial intelligence making it possible for the giants of industry and tech to be bigger and more profitable, while relentlessly squeezing out the need for human labor. If all current trends hold, people will have no choice but to start to re-imagine their place in society. And though it may seem counter-intuitive, the answers to these questions will represent a giant societal leap forward. As the world pushes forward into the age of algorithms with a declining need for human labor, the stage is set for what comes next — a return to what brings us closer to being human; a great resurgence in the arts, entrepreneurship, and creativity; a global renaissance.
What is the mathematical metaphor that dominates us in the post-modern age? How will the math of today affect our cultural future? I propose that the Science of Complexity, also known as Chaos Theory, provides many concepts which help to give insight into the context and direction of contemporary culture, as well as providing new technologies, methodologies, and metaphors for the production of valid work and theory. What tools can it provide us, both practically and intellectually? Perhaps we should first ask what it is that we look would look for in such a paradigm.
Advances in the scientific study of chaos have been important motivators/roots of the modern study of complex systems. There exists some confusion about the relationship of chaos and complexity. Chaos can be more or less strictly defined. A reasonably strict definition is that chaos deals with deterministic systems whose trajectories diverge exponentially over time. This property is expected to be found in the behavior of complex systems. However, how it can be related to various properties of complex systems continues to be an important area of research. Models of chaos generally describe the dynamics of one (or a few) variables which are real (ie represented by a decimal number). Using these models some characteristic behaviors of their dynamics can be found.