Collective Intelligence

Collective intelligence
is a shared or group intelligence that emerges from the
collaboration and competition of many individuals. Collective intelligence appears
in a wide variety of forms of consensus decision making in bacteria, animals, humans,
and computer networks. The study of collective intelligence may properly be considered
a subfield of sociology, of business, of computer science, of mass communications and
of mass behavior—a field that studies collective behavior from the level of quarks to
the level of bacterial, plant, animal, and human societies.


Collective Intelligence means many things to many people. It may refer to the capacity of human communities to evolve towards higher order complexity and integration through collaboration and innovation.
One of the most intriguing aspects of collective intelligence is its relative independence from individual intelligence.


One measure sometimes applied, especially by more artificial intelligence focused theorists,
is a "collective intelligence quotient" (or "cooperation quotient")—which presumably can
be measured like the "individual" intelligence quotient (IQ)—thus making it possible to
determine the marginal extra intelligence added by each new individual participating in
the collective, thus using metrics to avoid the hazards of group think and stupidity.

In 2001, Tadeusz (Ted) Szuba from the AGH University in Poland proposed a formal model for
the phenomenon of Collective Intelligence. It is assumed to be an unconscious, random,
parallel, and distributed computational process, run in mathematical logic by the social
structure.


In this model, beings and information are modeled as abstract information molecules
carrying expressions of mathematical logic. They are quasi-randomly displacing due to
their interaction with their environments with their intended displacements.
Their interaction in abstract computational space creates multithread inference process
which we perceive as Collective Intelligence. Thus, a non-Turing model of computation is
used. This theory allows simple formal definition of Collective Intelligence as the
property of social structure and seems to be working well for a wide spectrum of beings,
from bacterial colonies up to human social structures. Collective Intelligence considered
as a specific computational process is providing a straightforward explanation of several
social phenomena. For this model of Collective Intelligence, the formal definition of IQS
(IQ Social) was proposed and was defined as "the probability function over the time and
domain of N-element inferences which are reflecting inference activity of the social
structure." While IQS seems to be computationally hard, modeling of social structure in
terms of a computational process as described above gives a chance for approximation.
Prospective applications are optimization of companies through the maximization of their
IQS, and the analysis of drug resistance against Collective Intelligence of bacterial
colonies.