levy, pierre (2010) theoretical framework for a future computational collective intelligence

8/13/2019 LEVY, Pierre (2010) Theoretical Framework for a Future Computational Collective Intelligence

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Theoretical Framework for a FutureComputational Collective Intelligence

Pierre Levy (01/03/10) em Pierre Levy Posteroushttp://pierrelevy.posterous.com/theoretical-framework-for-a-future-computatio

1) Difference between Collective Computational Intelligence

and Computational Collective Intelligence

To avoid any misunderstanding I would like to begin with a clear

distinction between what I mean by Collective Computational

Intelligence and Computational Collective Intelligence.

a) Collective computational intelligence involves collaboration

between software agents, with a new level of computational

intelligence emerging form their collaboration. These technologies

involve swarm intelligence, ant colony simulation, web services, grid

computing, distributed cloud computing and multi-agent computing in

general.

b) Computational collective intelligence is a more multidisciplinary

field. Its subject is the understanding of human collective intelligence

and its augmentation by the means of ubiquitous distributed

automatic symbol manipulation. Even if computational collective

intelligence involves the use and development of collective

computational intelligence, its scope is broader because it is not

concerned only by computer engineering but promotes a strong

collaboration between computing on the one hand and humanities

and social sciences on the other hand.

2) Human Symbolic cognition

The main difference between animal cognition and human cognition is

that human beings are able to manipulate cultural symbolic systems

like languages, musical systems, rituals, legal systems, technologies,

etc. Animal cognition is obviously characterized by categorization and

memorization of sense data. But animal memory is mainly limited tothe individual and its categorization stays implicit. By contrast, in


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human cognition, sense data are explicitly categorizedby the use of

symbolic systems and symbolic memory can be shared inside

communities and between generations. As symbolic systems are

created and maintained at the social scale, human collective

intelligence involves a distributed and socially coordinated processing

of symbols (recording, transformation and transmission). This

personal and collective symbolic processing bears three

interdependent main fruits: reflexivity, dialogue and narrativity.

a) Reflexivity

The main source of reflexivity is the syntactic complexity and

semantic diversity of human languages. Reflexivity implies:- the ability to create and recreate symbolic maps of the

phenomenal world (the sensori-motor experience),

- the self-referential ability to map one's own symbolic

cognition,

- the ability to be aware of one's own ignorance, to question

one's own mental models and to ask questionsin general.

b) Dialogue

Dialogue is based on the partaking of symbolic systems - and notably

common languages - among human communities. Dialogue includes:

- exchange of ideas and narratives,

- negotiation about meaning and practical decisions,

- common understanding of complex models,

- common norms for reasoning and interpretation

- representation of the other's cognitive processes.

c) Narrativity

Narrativity is based on the ability to model complex causal

phenomena at the symbolic level. This involves the identification of

actors, objects, qualities and processes and the evocation of their

complex interaction through the virtual space-time of narratives.

Through all its various forms (that are not limited to the traditional

tales) narrativity is the main human tool for knowledge organization.


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Based of symbolic manipulation, reflexivity, dialogue and narrativity

make the natural human collective intelligence more powerful than

the animal collective intelligence.

3) The Digital Medium

Information technology augments natural human collective

intelligence by enhancing its ability to record, process and transmit

symbols. Information technology gives rise to an artificial human

collective intelligence. Artificial human collective intelligence began

with the use of writing systems, it grew with the printing press and

electronic media, it is now related to an universally distributed digital

medium.

The main idea behind computational collective intelligence is that the

digital medium is integrating all previous media and that it can

augment in an unprecedented way human collective intelligence by

harnessing the power of ubiquitous digital data storage and automatic

manipulation on these data. But as the digital medium is only one or

two generations old, we still don't have the cultural symbolic systems

that will help us to exploit fully the new availability of automaticsymbol manipulation. In particular, we know how to augment

numerical calculus and logical reasoning by the way of automatic

computation. But what about hyper-reflexivity of computational

collective intelligence processes? What about trans-cultural and trans-

linguistic dialogue on shared digital data? What about new kinds of

hyper-narrativity harnessing the ubiquitous availability of multimedia

data and computational power? We have already a digital medium

but still no hypercortex.

4) The IEML Semantic Sphere

a) Addressing layers of thedigital medium1) The first layer assigns addresses to bits in the physical storage

systems of automatic symbol manipulators. It is the operating

systemsthat take care of this addressing layer. This layer has been

set-up in the middle of the XXe century.


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2) The second layer assigns addresses to the automatic symbol

manipulators in theglobal digital telecommunication network. It is of

course the Internet protocolthat takes care of this addressing layer.

Even it has been invented at the end of the 1960 decade, the

Internet emerged as an universal addressing system only during the

years 1980, at the time of the personal computing revolution.

3) The third layer, the WWW, assigns precise universal addresses to

Pages (URLs), allowing the hyperlinking from any URL to any other.

The WWW has been widely adopted from the middle of the nineties of

the last century. A powerful generalization of the WWW is theWeb of

data. Through the data formats XML, RDF and OWL, the Web of data

insures a better interoperability between data addressed by URLs.The Web of data (particularly regarding RDF and OWL) is still in a

phase of implementation.

4) I'm pleading here for the adoption of a fourth layer of addressing:

the addressing ofconcepts. This new addressing layer would be based

on IEML (Information Economy Meta Language), an artificial symbolic

system that I have designed and that is theoretically able to express

any kind of meaning in a formal computable way. The main differencebetween the layer of data - addressed by URLs - and the layer of

semantic metadata - addressed by IEML USLs (Uniform Semantic

Locators) - is that URLs are opaque by design and that USLs are

transparent by design.

b) Transparency by design

All the nodes (USLs) of the IEML semantic sphere are variables of the

same semantic group of transformation and the computable circuits

between these nodes describe paradigmatic relations (set-subset

relations, etymologic relations, several kinds of symmetric relations,

serial relations) and syntagmatic relations (relations between the

elements of hyper-propositions and hyper-narratives).

The IEML semantic sphere presents itself as an immense closed

structure of intersecting syntagmatic and paradigmatic pipelines that

branch out from nodes (IEML USLs) of which each is a separate


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variable in a system of symmetrical and calculable transformations.

One can think of the syntax of IEML as a virtual machine capable of

computing the vast network of fractal complexity of the semantic

sphere. This syntactic machine needs to be provided with a

dictionary. The dictionary establishes a correspondence between IEML

and natural languages and sets the details of internal connections of

the semantic sphere. Each point, junction or node of the IEML

semantic sphere is at the center of a multitude of pathways of

calculable transformations. Along these pathways of transformation,

each "step" from one intersection to another is the variable of a

discrete function. Step by step and from one to the next, these paths

connect each point to the entire mass of all the other points. In the

centrifugal direction, an intersection point is at the singular origin of astar of transformation that generates the entire sphere. In the

centripetal direction, a junction-point functions as a universal

vanishing point of the noosphere, since there is a computable path of

transformation that leads to it from any other point.

c) A model of computational collective intelligence

I propose a model of computational collective intelligence in which anonline creative conversation actualizes the junction of (a) the

symbolic cognition based on the natural cortex and (b) the

computational symbolic cognition based on a mechanical

hypercortext. The structure of the natural symbolic cognition has

already been sketched. The computational symbolic cognition has

hopefully the same structure as the natural cognition.

The Web of data is the equivalent of the sense data of personal

natural cognition. It is of course multimedia. It is also opaque (or

implicit) because its addresses are not the variables of a transparent

group of transformations.

The IEML semantic sphere is the equivalent of the discursive explicit

symbolic layer in the natural cognition based on the biological cortex.

But as it is based on the digital medium, it has been designed from

the beginning to exploit fully its distributed computing power and to

augment human reflexivity, dialogue and narrativity at the scale of


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the current online creative conversation. It can be used to describe,

map and organize the digital multimedia memory from any semantic

perspective or universe of discourse. It is also able to make these

different perspectives and universe of discourse automatically inter-

operable. Moreover, its circuit structure allows for the design of

varied information economy games organizing the circulation of

symbolic energy. These information economy games will take as their

imput the activity of players tagging data and assessing their value.

Computational collective intelligence implies the categorization of

multimedia data by semantic metadata and the multimedia

representation of semantic information economy.

My guess is that we would be able to build a hypercortex augmenting

decisively our human collective intelligence only if we grow a

transparent hypertextual sphere of semantic metadata, the nodes of

its graph being the variables of the same group of transformation.

Needless to say, the growth of an hypercortex enabled by a semantic

sphere of transparent metadata would be a huge cultural and

technical international endeavor. IEML is only the proof by a real

example that the success of such an endeavor is possible.

levy, pierre (2010) theoretical framework for a future computational collective intelligence

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