Emergence happens through an interdependant circulation of information between two levels of complexity. A code translates and betrays information in both directions: bottom-up and top-down.
According to our model, human collective intelligence emerges from natural evolution. The lower level of quantic complexity translates into a higher level of molecular complexity through the atomic stabilization and coding. There are no more than 120 atomic elements that explain the complexity of matter by their connections and reactions. The emergence of the next level of complexity – life – comes from the genetic code that is used by organisms as a trans-generational memory. Communication in neuronal networks translates organic life into conscious phenomena, including sense data, pleasure and pain, desire, etc. So emerges the animal life. Let’s note that organic life is intrinsically ecosystemic and that animals have developed many forms of social or collective intelligence. The human level emerges through the symbolic code : language, music, images, rituals and all the complexity of culture. It is only thank to symbols that we are able to conceptualize phenomena and think reflexively about what we do and think. Symbolic systems are all conventional but the human species is symbolic by nature, so to speak. Here, collective intelligence reaches a new level of complexity because it is based on collaborative symbol manipulation.
[WARNING: the next 5 paragraphs can be found in “collective intelligence for educators“, if you have already read them, go to the next slide: “algorithmic medium”] The above slide describes the successive steps in the emergence of symbolic manipulation. As for the previous slide, each new layer of cultural complexity emerges from the creation of a coding system.
During the longest part of human history, the knowledge was only embedded in narratives, rituals and material tools. The first revolution in symbolic manipulation is the invention of writing with symbols endowed with the ability of self-conservation. This leads to a remarquable augmentation of social memory and to the emergence of new forms of knowledge. Ideas were reified on an external surface, which is an important condition for critical thinking. A new kind of systematic knowledge was developed: hermeneutics, astronomy, medicine, architecture (including geometry), etc.
The second revolution optimizes the manipulation of symbols like the invention of the alphabet (phenician, hebrew, greek, roman, arab, cyrilic, korean, etc.), the chinese rational ideographies, the indian numeration system by position with a zero, paper and the early printing techniques of China and Korea. The literate culture based on the alphabet (or rational ideographies) developed critical thinking further and gave birth to philosophy. At this stage, scholars attempted to deduce knowledge from observation and deduction from first principles. There was a deliberate effort to reach universality, particularly in mathematics, physics and cosmology.
The third revolution is the mecanization and the industrialization of the reproduction and diffusion of symbols, like the printing press, disks, movies, radio, TV, etc. This revolution supported the emergence of the modern world, with its nation states, industries and its experimental mathematized natural sciences. It was only in the typographic culture, from the 16th century, that natural sciences took the shape that we currently enjoy: systematic observation or experimentation and theories based on mathematical modeling. From the decomposition of theology and philosophy emerged the contemporary humanities and social sciences. But at this stage human science was still fragmented by disciplines and incompatible theories. Moreover, its theories were rarely mathematized or testable.
We are now at the beginning of a fourth revolution where an ubiquitous and interconnected infosphere is filled with symbols – i.e. data – of all kinds (music, voice, images, texts, programs, etc.) that are being automatically transformed. With the democratization of big data analysis, the next generations will see the advent of a new scientific revolution… but this time it will be in the humanities and social sciences. The new human science will be based on the wealth of data produced by human communities and a growing computation power. This will lead to reflexive collective intelligence, where people will appropriate (big) data analysis and where subjects and objects of knowledge will be the human communities themselves.
Let’s have a closer look at the algorithmic medium. Four layers have been added since the middle of the 20th century. Again, we observe the progressive invention of new coding systems, mainly aimed at the addressing of processors, data and meta-data.
The first layer is the invention of the automatic digital computer itself. We can describe computation as « processing on data ». It is self-evident that computation cannot be programmed if we don’t have a very precise addressing system for the data and for the specialized operators/processors that will transform the data. At the beginning these addressing systems were purely local and managed by operating systems.
The second layer is the emergence of a universal addressing system for computers, the Internet protocol, that allows for exchange of data and collaborative computing across the telecommunication network.
The third layer is the invention of a universal system for the addressing and displaying of data (URLs, http, html). Thank to this universal addressing of data, the World Wide Web is a hypertextual global database that we all create and share. It is obvious that the Web has had a deep social, cultural and economic impact in the last twenty years.
The construction of the algorithmic medium is ongoing. We are now ready to add a fourth layer of addressing and, this time, it will be a universal addressing system for semantic metadata. Why? First, we are still unable to resolve the problem of semantic interoperability across languages, classifications and ontologies. And secondly, except for some approximative statistical and logical methods, we are still unable to compute semantic relations, including distances and differences. This new symbolic system will be a key element to a future scientific revolution in the humanities and social sciences, leading to a new kind of reflexive collective intelligence for our species. Moreover, it will pave the way for the emergence of a new scientific cosmos – not a physical one but a cosmos of the mind that we will build and explore collaboratively. I want to strongly underline here that the semantic categorization of data will stay in the hands of people. We will be able to categorize the data as we want, from many different point of views. All that is required is that we use the same code. The description itself will be free.
Let’s examine now the future emerging algorithmic intelligence. This new level of symbolic manipulation will be operated and shared in a mixed environment combining virtual worlds and augmented realities. The two lower levels of the above slide represent the current internet: an interaction between the « internet of things » and the « clouds » where all the data converge in an ubiquitous infosphere… The two higher levels, the « semantic sensorium » and the « reflexive collective intelligence » depict the human condition that will unfold in the future.
The things are material, localized realities that have GPS addresses. Here we speak about the smart territories, cities, buildings, machines, robots and all the mobile gadgets (phones, tablets, watches, etc.) that we can wear. Through binary code, the things are in constant interaction with the ubiquitous memory in the clouds. Streams of data and information processing reverberate between the things and the clouds.
When the data will be coded by a computable universal semantic addressing system, the data in the clouds will be projected automatically into a new sensorium. In this 3D, immersive and dynamic virtual environment we will be able to explore through our senses the abstract relationships between the people, the places and the meaning of digital information. I’m not speaking here of a representation, reproduction or imitation of the material space, like, for example, in Second Life. We have to imagine something completely different: a semantic sphere where the cognitive processes of human communities will be modeled. This semantic sphere will empower all its users. Search, knowledge exploration, data analysis and synthesis, collaborative learning and collaborative data curation will be multiplied and enhanced by the new interoperable semantic computing.
We will get reflexive collective intelligence thank to a scientific computable and transparent modeling of cognition from real data. This modeling will be based on the semantic code, that provides the « coordinate system » of the new cognitive cosmos. Of course, people will not be forced to understand the details of this semantic code. They will interact in the new sensorium through their prefered natural language (the linguistic codes of the above slide) and their favorite multimedia interfaces. The translation between different languages and optional interface metaphors will be automatic. The important point is that people will observe, analyze and map dynamically their own personal and collective cognitive processes. Thank to this new reflexivity, we will improve our collaborative learning processes and the collaborative monitoring and control of our physical environments. And this will boost human development!
The above slide represents the workings of a collective intelligence oriented towards human development. In this model, collective intelligence emerges from an interaction between two levels: virtual and actual. The actual is addressed in space and time while the virtual is latent, potential or intangible. The two levels function and communicate through several symbolic codes. In any coding system, there are coding elements (signs), coded references (things) and coders (being). This is why both actual and virtual levels can be conceptually analysed into three kinds of networks: signs, beings and things.
The actual human development can be analysed into a sphere of messages (signs), a sphere of people (beings) and a sphere of equipments – this last word understood in the largest possible sense – (things). Of course, the three spheres are interdependent.
The virtual human development is analysed into a sphere of knowledge (signs), a sphere of ethics (being) and a sphere of power (things). Again, the three spheres are interdependent.
Each of the six spheres is further analysed into three subdivisions, corresponding to the sub-rows on the slide. The mark S (sign) points to the abstract factors, the mark B (being) indicates the affective dimensions and the mark T (thing) shows the concrete aspects of each sphere.
All the realities described in the above table are interdependent following the actual/virtual and the sign/being/thing dialectics. Any increase of decrease in one « cell » will have consequences in other cells. This is just an example of the many ways collective intelligence will be represented, monitored and made reflexive in the semantic sensorium…
To dig into the philosophical concept of algorithmic intelligence go there